﻿| 文档版本 | 修订日期   | 修订内容 | 适用主控软件版本 （若不满足请前往官网下载中心获取最新版本主控软件包进行升级） |
| -------- | ---------- | -------- | ----------------------------------------------------------------------------- |
| V1.0     | 2026.02.27 | 初版     | V2.1.21 及以上                                                                |
| V1.1     | 2026.07.17 | 1. 删除 MCP Server<br>2. 新增关闭相机驱动自启动功能 | V2.2.11 及以上                 |
| V1.2     | 2026.07.30 | 1. 补充获取相机数据步骤说明 | V2.2.11 及以上                                      |
| V1.3     | 2026.09.16 | 1. 新增音频设备接口 | V2.2.11 及以上                                      |

---

# 1 大模型调用接口

## 1.1 内置大模型

| 模型             | 备注                                                                                                                                 |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------ |
| qwen2.5:3b       | 由阿里云推出的通义千问 2.5 系列模型，参数量为 30 亿。具备较强的语言理解和生成能力，适用于文本生成、对话交互等场景。                  |
| qwen2.5:1.5b     | 通义千问 2.5 系列中参数量为 15 亿的模型，相对轻量，在一些对计算资源要求不高的场景中也能有较好表现 。                                 |
| qwen2.5:0.5b     | 参数量为 5 亿的轻量级模型，便于在终端设备或资源有限的环境下运行。                                                                    |
| llama3.2:3b      | Meta 公司开发的大语言模型 LLaMA 3.2 版本中的 30 亿参数模型，在自然语言处理任务上表现出色，开源特性使得开发者可以基于它进行二次开发。 |
| llama3.2:1b      | LLaMA 3.2 系列的 10 亿参数模型，模型规模较小，训练和推理速度相对较快。                                                               |
| deepseek-r1:1.5b | DeepSeek 推出的模型，参数量 15 亿，在多种语言处理任务中具备一定的竞争力。                                                            |

## 1.2 大模型调用

Oli 已通过 ollama 在本地完成上述大模型部署，只需将您的设备连接至与机器人相同的网络，即可按以下方法进行调用。

### 1.2.1 使用 Curl 调用

```
curl http://10.192.1.3:11434/api/generate \
  -H "Content-Type: application/json" \
  -d '{
        "model": "qwen2.5:3b",
        "prompt": "请写一首描述春天的四言绝句？",
        "temperature": 0.7,
        "max_tokens": 200,
        "stream": false
      }'
```

### 1.2.2 使用 Python 调用

```
import requests

url = "http://10.192.1.3:11434/api/generate"
data = {
    "model": "qwen2.5:3b",
    "prompt": "请写一首描述春天的四言绝句？",
    "temperature": 0.7,
    "max_tokens": 200,
    "stream": False
}

response = requests.post(url, json=data)
if response.status_code == 200:
    print(str(response.json()['response']))
else:
    print(f"Request failed with status code: {response.status_code}, Error: {response.text}")
```

### 1.2.3 使用 C++ 调用

以 Ubuntu 20.04 及以上系统版本为例：

- **安装依赖**

```
sudo apt-get install libcurl4-openssl-dev nlohmann-json3-dev 
```

- **代码实现(llm_demo.cpp)**

```
#include <iostream>
#include <string>
#include <curl/curl.h>      // HTTP client library
#include <nlohmann/json.hpp> // JSON parsing

using json = nlohmann::json;

// Callback to handle HTTP response data
static size_t WriteCallback(void* data, size_t size, size_t nmemb, std::string* buf) {
    buf->append((char*)data, size * nmemb);
    return size * nmemb;
}

int main() {
    CURL* curl = curl_easy_init();
    if (!curl) {
        std::cerr << "CURL init failed" << std::endl;
        return 1;
    }

    // 1. Configure API endpoint
    const std::string url = "http://10.192.1.3:11434/api/generate";
    
    // 2. Prepare JSON payload
    json req = {
        {"model", "qwen2.5:3b"},
        {"prompt", "请写一首描述春天的四言绝句？"},
        {"temperature", 0.7},
        {"max_tokens", 200},
        {"stream", false}
    };
    std::string payload = req.dump();

    // 3. Set CURL options
    curl_easy_setopt(curl, CURLOPT_URL, url.c_str());
    curl_easy_setopt(curl, CURLOPT_POSTFIELDS, payload.c_str());
    curl_easy_setopt(curl, CURLOPT_POSTFIELDSIZE, payload.size());

    // 4. Add HTTP headers
    struct curl_slist* headers = nullptr;
    headers = curl_slist_append(headers, "Content-Type: application/json");
    curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);

    // 5. Capture response
    std::string response;
    curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, WriteCallback);
    curl_easy_setopt(curl, CURLOPT_WRITEDATA, &response);

    // 6. Execute request
    CURLcode res = curl_easy_perform(curl);

    // 7. Process result
    if (res == CURLE_OK) {
        try {
            json resp_json = json::parse(response);
            std::cout << "Result: " << resp_json["response"] << std::endl;
        } catch (const json::exception& e) {
            std::cerr << "JSON error: " << e.what() << std::endl;
        }
    } else {
        std::cerr << "HTTP error: " << curl_easy_strerror(res) << std::endl;
    }

    // 8. Cleanup
    curl_slist_free_all(headers);
    curl_easy_cleanup(curl);
    return 0;
}
```

- **编译并运行**

```
# Compile with C++11 support
g++ -std=c++11 -o llm_demo llm_demo.cpp -lcurl

# Execute
./llm_demo
```

# 2 通讯架构图

下图呈现了开发者的电脑与机器人本体的系统组成及交互关系。开发电脑部分涵盖运控算法节点和软件业务逻辑实现模块，通过 `上层应用协议接口` 和 `limxsdk-lowlevel` 的数据通讯控制机器人本体的运动。机器人本体由数据交换机、主控电脑及各类硬件组件构成，主控电脑负责协调各组件运行。

| 中文版 | 英文版 |
| --- | --- |
| ![图片](data:image/webp;base64,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) | ![图片](data:image/webp;base64,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) |

# 3 上层应用协议接口

机器人通过 WebSocket 通信端口 `5000` 来接收用户端请求指令，例如让机器人站起、蹲下、行走等。

WebSocket 是一种实时通信协议，在机器人和用户端之间建立长连接，以便快速有效地传输控制信息和数据。如下图所示：

![图片](data:image/webp;base64,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)

---

## 3.1 坐标说明

- 如无特别说明，双臂末端的位置、姿态，均基于机器人的 base 坐标系。
- SN 开头为 HU 的人型机器人 base 坐标系的定义。
- base 坐标系原点为 URDF 文件中定义的 base_link，坐标系标准为右手坐标系 / [REP-103](https://www.ros.org/reps/rep-0103.html) 坐标系。

## 3.2 通信协议格式

当机器人通过 WebSocket 接收客户端指令时，采用 JSON 数据协议进行信息传递。

### 3.2.1 请求数据

| 请求数据格式包含字段 | 描述                                                                                                                                                                                                                           |
| -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `accid`              | 机器人唯一序列号，标识机器人的唯一身份。                                                                                                                                                                                       |
| `title`              | 指令名称，以“`request_`”为前缀。                                                                                                                                                                                             |
| `timestamp`          | 指令发出时间戳，单位为毫秒。                                                                                                                                                                                                   |
| `guid`               | 指令的唯一标识符，用于区分不同的请求指令；如果是同步接口，则需要在“response_xxx”响应消息中通过 guid 字段将值带回给客户端；客户端接收到响应消息后，可以通过比较 guid 字段的值是否与请求指令中的值相同来判断指令是否执行完成。 |
| `data`               | 存放请求指令的数据内容。可以根据具体需求包含多个子字段，以存放请求指令所需的数据内容，例如执行动作的参数、发送消息的文本内容等等。                                                                                             |

**请求数据代码示例：**

```
{
  "accid": "HU_D02_001", # 机器人唯一序列号，标识机器人的唯一身份
  "title": "request_xxx",   # 指令名称，以“request_”为前缀
  "timestamp": 1672373633989, # 指令发出时间戳，单位为毫秒
  "guid": "746d937cd8094f6a98c9577aaf213d98", # 指令的唯一标识符，用于区分不同的请求指令
  "data": {}  # 存放请求指令的数据内容
}
```

### 3.2.2 响应数据

| 响应数据格式包含字段 | 描述                                                                                                                                               |
| -------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| `accid`              | 机器人唯一序列号，标识机器人的唯一身份。                                                                                                           |
| `title`              | 指令名称，以“`response_`”为前缀。                                                                                                                |
| `timestamp`          | 指令发出时间戳，单位为毫秒。                                                                                                                       |
| `guid`               | 与对应请求指令的 `guid` 值相同。                                                                                                                     |
| `data`               | 至少应该包含一个“result”子字段，用于存放请求指令的执行结果数据。如果有需要，还可以包含其他子字段，例如错误码、错误信息等用于描述操作结果的信息。 |

**响应数据代码示例：**

```json
{
  "accid": "HU_D02_001",   # 机器人唯一序列号，标识机器人的唯一身份
  "title": "response_xxx",  # 指令名称，以“response_”为前缀
  "timestamp": 1672373633989, # 指令发出时间戳，单位为毫秒
  "guid": "746d937cd8094f6a98c9577aaf213d98", # 与对应请求指令的guid值相同
  "data": { # 存放响应指令的具体数据内容
    "result": "success"  # “result” 用于存放请求指令处理是否成功，它的值为：“success 或 fail_xxx”
  }
}
```

### 3.2.3 消息推送

机器人主动向客户端发送信息的过程。这些信息可以包括机器人的序列号、当前运行状态、执行的操作等数据。通过及时地向客户端发送这些信息，机器人可以帮助客户端更好地理解它的工作状态，从而更好地使用它提供的服务。

| 消息推送数据格式包含字段 | 描述                                                                             |
| ------------------------ | -------------------------------------------------------------------------------- |
| `accid`                  | 机器人唯一序列号，标识机器人的唯一身份。                                         |
| `title`                  | 指令名称，以“`notify_`”为前缀。                                                |
| `timestamp`              | 消息发出时间戳，单位为毫秒。                                                     |
| `guid`                   | 消息的 guid 值，唯一标识这条消息。                                               |
| `data`                   | 存放消息数据内容。可以根据具体需求包含多个子字段，以存放请求指令所需的数据内容。 |

**消息推送代码示例：**

```json
{
  "accid": "HU_D02_001",   # 机器人唯一序列号，标识机器人的唯一身份
  "title": "notify_xxx",  # 消息名称，以“notify_”为前缀
  "timestamp": 1672373633989, # 消息发出时间戳，单位为毫秒
  "guid": "746d937cd8094f6a98c9577aaf213d98", # 消息的guid值，唯一标识这条消息
  "data": { } # 存放消息数据内容
}
```

## 3.3 通信测试方法

Postman 是一个流行的 API 开发环境，可以用于测试 WebSocket 接口。

使用 Postman 测试 WebSocket 接口操作步骤：

1. 安装 postman，下载地址：[https://www.postman.com/downloads/?utm_source=postman-home](https://www.postman.com/downloads/?utm_source=postman-home)；
2. 打开 Postman，并创建一个 WebSocket 的请求；
3. 连接机器人无线网络  1. 机器人开机完成后，使用个人电脑连接机器人 Wi-Fi，名称格式通常为「HU_D02_xxx」
4. 输入 Wi-Fi 密码：`12345678`
5. 在请求的 URL 中输入 WebSocket 接口的地址，例如，“ws://10.192.1.2:5000”;
6. 在“Message”中，输入要发送的指令请求；
7. 单击“Send”按钮，发送请求指令；
8. 发送指令后，可以从服务器接收响应消息。使用 Postman 的响应窗口查看服务器返回的数据，并检查是否符合预期结果。![图片](data:image/webp;base64,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)

## 3.4 基础功能协议接口

### 3.4.1 连接 Wi-Fi 热点

#### 3.4.1.1 请求：request_connect_wifi

> 本协议用于向机器人路由器发起请求，指令路由器连接到指定 SSID 的 WiFi 热点并返回连接结果，支持机器人版本：2.1.3 及以上。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_connect_wifi",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": { 
      "wifi_band": "0",  # WiFi频段：0=5GHz，1=2.4GHz
      "wifi_ssid": "Limx-Guests",  # 目标WiFi的SSID（WiFi名称），区分大小写，需与实际热点一致
      "wifi_password": "LimX2024",  # 目标WiFi的密码，WPA2-PSK加密方式的密码
      "router_admin_password": "12345678"  # 机器人路由器的管理员密码
  }
}
```

#### 3.4.1.2 响应：response_connect_wifi

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_connect_wifi",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功
                           # fail_no_wifi_band: 没有指定频段
                           # fail_no_wifi_ssid: 没有指定ssid
                           # fail_no_wifi_password: 没有指定密码
                           # fail_no_router_admin_password: 没有指定密码
  }
}
```

#### 3.4.1.3 消息推送：无

### 3.4.2 查询 Wi-Fi 连接状态

> 本协议用于客户端向机器人路由器发起 WiFi 连接状态查询请求，路由器接收请求后反馈当前已连接 WiFi 的核心状态信息，包括关联 SSID、信号强度及连接结果，支撑客户端实时感知设备网络连接状态。客户端发起 WiFi 连接状态查询，需携带机器人路由器管理员密码完成身份校验。

#### 3.4.2.1 请求：request_wifi_connection_status

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_wifi_connection_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "router_admin_password": "12345678"  # 机器人路由器的管理员密码
  }
}
```

#### 3.4.2.2 响应：response_wifi_connection_status

> 机器人路由器接收查询请求后，返回当前 WiFi 实际连接状态，供客户端解析展示或后续业务处理。

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_wifi_connection_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "ssid": "Limx-Guests",
      "signal": -56,        # 单位dBm
      "result": "success"   # success: 成功
                            # fail_disconnected
  }
}
```

#### 3.4.2.3 消息推送：无

### 3.4.3 进入准备状态

> 机器人缓慢摆出准备姿势。

#### 3.4.3.1 请求：request_prepare

> 控制机器人进入“站姿”，可接受速度指令控制行走。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_prepare",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": { }
}
```

#### 3.4.3.2 响应：response_prepare

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_prepare",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

#### 3.4.3.3 消息推送：无

### 3.4.4 控制机器人行走

#### 3.4.4.1 进入行走模式

机器人进入行走模式，可以接收速度指令。

##### 3.4.4.1.1 请求：request_set_walk_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_walk_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.4.1.2 响应：response_set_walk_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_walk_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.4.4.1.3 消息推送：无

#### 3.4.4.2 控制机器人行走

在移动操作模式下，通过此协议控制机器人行走。请注意，在全身操作模式下，此协议接口无效。

##### 3.4.4.2.1 请求：request_set_walk_vel

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_walk_vel",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "x": 0.0,   #  前进后退速度比值，取值范围[-1, 1]
    "y": 0.0,   #  横向行走速度比值，取值范围[-1, 1]
    "yaw": 0.0  #  旋转角速度比值，取值范围[-1, 1]
  }
}
```

##### 3.4.4.2.2 响应：response_set_walk_vel

指令执行失败时返回此消息，成功执行则无返回。

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_walk_vel",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "fail_motor"  # fail_imu: IMU 错误, fail_motor: 电机错误
  }
}
```

##### 3.4.4.2.3 消息推送：无

### 3.4.5 进入阻尼模式

机器人所有电机停止主动运动，摆动时有明显阻尼感。

#### 3.4.5.1 请求：request_damping

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_damping",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.4.5.2 响应：response_damping

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_damping",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: 电机错误
  }
}
```

#### 3.4.5.3 消息推送：无

### 3.4.6 进入零力矩模式

机器人所有电机停止主动运动，摆动时没有阻尼感。

#### 3.4.6.1 请求：request_zero_torque

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_zero_torque",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.4.6.2 响应：response_zero_torque

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_zero_torque",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: 电机错误
  }
}
```

#### 3.4.6.3 消息推送：无

### 3.4.7 进入坐下指令

#### 3.4.7.1 请求：request_from_stand_to_sit

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_from_stand_to_sit",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.4.7.2 响应：response_from_stand_to_sit

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_from_stand_to_sit",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: 电机错误
  }
}
```

#### 3.4.7.3 消息推送：无

### 3.4.8 进入站立指令

> **提示：**
>
> 接口功能：启动机器人使用，机器人开机后调用该接口进入站立状态。
> 参数 mode：[lying：机器人躺着    hanging：机器人吊着   sit: 机器人坐着]
> 返回：已站起后返回

#### 3.4.8.1 请求：request_standup

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_standup",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "mode": "lying" // "lying"/"sitting"：机器人当前躺着/坐着  or 
                      // "hanging"：机器人当前状态吊着
                      // 若没有"mode" 字段 默认机器人状态是"sitting"坐着
  }
}
```

#### 3.4.8.2 响应：response_standup

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_standup",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: 电机错误
                          # fail_invalid_cmd：参数错误
                          # fail_invalid_mode：机器人状态错误
                          # fail_timeout：执行超时错误
  }
}
```

#### 3.4.8.3 消息推送：无

### 3.4.9 进入躺着指令

#### 3.4.9.1 请求：request_lie_down

> Walk 状态下可以调用该接口

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_lie_down",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.4.9.2 响应：response_lie_down

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_lie_down",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: 电机错误
  }
}
```

#### 3.4.9.3 消息推送：无

### 3.4.10 机器人校零指令

#### 3.4.10.1 请求：request_calibrate

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_calibrate",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.4.10.2 响应：response_calibrate

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_calibrate",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: 电机错误
  }
}
```

#### 3.4.10.3 消息推送：notify_calibrate

校零完成后，推送此消息。

```python
{
  "accid": "HU_D04_01_001",
  "title": "notify_calibrate",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"
  }
}
```

### 3.4.11 机器人舞蹈

#### 3.4.11.1 切换机器人到舞蹈模式

##### 3.4.11.1.1 请求：request_enter_dance_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_enter_dance_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    # 0：退出舞蹈模式
    # 1：进入舞蹈模式 
    "mode": 0
  }
}
```

##### 3.4.11.1.2 响应：response_enter_dance_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_enter_dance_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

##### 3.4.11.1.3 消息推送：无

#### 3.4.11.2 获取舞蹈列表

##### 3.4.11.2.1 请求：request_get_dance_list

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_dance_list",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.11.2.2 响应：response_get_dance_list

```json
{
    "accid": "HU_D04_01_001",
    "title": "response_get_dance_list",
    "guid": "746d937cd8094f6a98c9577aaf213d98",
    "timestamp": 1672373633989,
    "data": {
        "result": "success",
        "code": 0,
        "dances": [
            {
                "id": "DAN-14",
                "index": 0,
                "name": "\u70ed\u70c8",
                "english_name": "One and Only Dance",
                "rc_mapping": "one_and_only_dance"
            },
            {
                "id": "DAN-08",
                "index": 1,
                "name": "\u4f4e\u4fd7\u5c0f\u8bf4",
                "english_name": "Pulp Fiction Dance",
                "rc_mapping": "pulp_fiction_dance"
            }
        ]
    }
}
```

#### 3.4.11.3 机器人跳舞

##### 3.4.11.3.1 请求：request_dance

> **提示：**
>
> 1. 执行前置条件：当前处于动作库模式
> 2. 适用于主控 V2.1.21 及以上版本

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_dance",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "name": "one_and_only_dance"  # rc_mapping 字段的舞蹈名称
  }
}
```

##### 3.4.11.3.2 响应：response_dance

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_dance",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

##### 3.4.11.3.3 消息推送：notify_dance

跳完舞蹈或执行过程中失败推送此消息。

```json
{
  "accid": "HU_D04_01_001",
  "title": "notify_dance",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

### 3.4.12 机器人原地踏步

#### 3.4.12.1 开启原地踏步

##### 3.4.12.1.1 请求：request_start_walktoggle

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_start_walktoggle",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.12.1.2 响应：response_start_walktoggle

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_start_walktoggle",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

##### 3.4.12.1.3 消息推送：无

#### 3.4.12.2 停止原地踏步

##### 3.4.12.2.1 请求：request_stop_walktoggle

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_stop_walktoggle",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.12.2.2 响应：response_stop_walktoggle

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_stop_walktoggle",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

### 3.4.13 机器人动作库

#### 3.4.13.1 动作打断

##### 3.4.13.1.1 请求：request_interrupt_action_joystick

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_interrupt_action_joystick",
  "timestamp": 1779355330784,
  "guid": "32cef03a-5563-4b21-9bbb-3e65a8c9ae9e",
  "data": {}
}
```

##### 3.4.13.1.2 响应：response_interrupt_action_joystick

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_interrupt_action_joystick",
  "guid": "32cef03a-5563-4b21-9bbb-3e65a8c9ae9e",
  "timestamp": 1779355330784,
  "data": {
    "result": "success"
  }
}
```

#### 3.4.13.2 获取动作库状态

> 接口说明：
>
> 1. 机器人进入动作库之后，处于动作库/原子执行/舞蹈中将显示："action_library_mode": "action_library"
> 2. 当机器人在执行原子动作中或者舞蹈中将显示： "action_library_state": "running"

##### 3.4.13.2.1 请求：request_get_action_library_status

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_action_library_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.13.2.2 响应：response_get_action_library_status

```json
{
  "accid": "HU_D04_01_001",
  "title": "get_action_library_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "action_library_mode": "action_library" //"remote_control"
      "action_library_state": "running"       //"idle"
      "result": "success" # fail_motor
  }
}
```

#### 3.4.13.3 执行动作库

> 接口说明：
> 1. 不在 Menu 会自动进入 Menu，动作执行完会保持 Menu；
> 2. 需配合 `request_get_action_library_status` 的 `action_library_state` 使用。

##### 3.4.13.3.1 请求：request_action_sync_stay_menu

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_action_sync_stay_menu",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "name": "one_and_only_dance"
  }
}
```

##### 3.4.13.3.2 响应：response_action_sync_stay_menu

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_action_sync_stay_menu",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success" # fail_motor
  }
}
```

#### 3.4.13.4 执行动作库（同步接口）

> 接口说明：
> 1. 当机器人处于不可执行动作库时，在 100ms 内返回失败响应；
> 2. 当机器人处于可执行动作库时（walk/motion library），在执行动作库之后返回响应。
> 3. 同步接口，会自动回到Walk，结束状态通过判断是否再Walk结束。

##### 3.4.13.4.1 请求：request_action_sync

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_action_sync",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "name": "one_and_only_dance,this_way_please"  
                                    # name:多个舞蹈/多个动作/舞蹈与动作混合,用“，”隔开
  }
}
```

##### 3.4.13.4.2 响应：response_action_sync

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_action_sync",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

#### 3.4.13.5 切换机器人到动作库模式

##### 3.4.13.5.1 请求：request_set_motion_engine

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_motion_engine",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    # 0：退出动作库模式
    # 1：进入动作库模式 
    "mode": 0
  }
}
```

##### 3.4.13.5.2 响应：response_set_motion_engine

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_motion_engine",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

##### 3.4.13.5.3 消息推送：无

#### 3.4.13.6 获取动作库列表

##### 3.4.13.6.1 请求：request_get_atomic_motion_list

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_atomic_motion_list",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.13.6.2 响应：response_get_atomic_motion_list

```json
{
    "accid": "HU_D04_01_001",
    "title": "response_get_atomic_motion_list",
    "guid": "746d937cd8094f6a98c9577aaf213d98",
    "timestamp": 287883835,
    "data": {
        "result": "success",
        "motion_list": [
            {
                "motion_index": 0,
                "motion_name_cn": "静止站立",
                "motion_name_en": "stand"
            },
            {
                "motion_index": 1,
                "motion_name_cn": "指引请这边走",
                "motion_name_en": "this_way_please"
            }
            ......
        ],
        "count": 2
    }
}
```

#### 3.4.13.7 执行机器人动作库动作

设置机器人为动作库模式后，可以执行机器人动作库中的动作。

##### 3.4.13.7.1 请求：request_execute_atomic_motion

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_execute_atomic_motion",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    # 动作名称
    "motion_name": "wave_greet_bye"
  }
}
```

##### 3.4.13.7.2 响应：response_execute_atomic_motion

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_execute_atomic_motion",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

##### 3.4.13.7.3 消息推送：notify_execute_atomic_motion

动作执行完成或执行过程中失败推送此消息。

```json
{
  "accid": "HU_D04_01_001",
  "title": "notify_execute_atomic_motion",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

### 3.4.14 机器人移动操作

#### 3.4.14.1 移动操作模式切换

在移动操作模式下您还可以控制机器人行走，但不能控制机器人的身高及腰部运动。

![图片](data:image/webp;base64,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)

##### 3.4.14.1.1 请求：request_set_ub_manip_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_ub_manip_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "mode": 0  # 0: 准备进入模式 1: 操作模式，开始跟踪末端位置 2: 准备退出模式
  }
}
```

##### 3.4.14.1.2 响应：response_set_ub_manip_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_ub_manip_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.4.14.1.3 消息推送：无

#### 3.4.14.2 移动操作控制

需要通过协议接口 `request_set_ub_manip_mode`，功能才生效。

- **参考坐标系示意图：**
  - 位置 —— base_link的原点（髋部下方正中间）
  - 坐标轴定义：红色为x方向：机器人前进方向；绿色为y方向：正方向向左；蓝色为z方向：竖直朝上

| <img src="data:image/webp;base64,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" alt="图片" width="228" height="367" /> | <img src="data:image/webp;base64,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" alt="图片" width="194" height="345" /> |

##### 3.4.14.2.1 请求：request_set_ub_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_ub_manip_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 参考坐标系定义：
      # 原点：base_link坐标系
      # 方向：x方向对齐机器人正前方，y方向朝向机器人左侧，z方向竖直向上
      #
      # 参数定义：
      # 头相对于参考坐标系的姿态，四元数[x,y,z,w]
      "head_quat": [0.0, 0.0, 0.0, 1.0],
    
      # 左手相对于参考坐标系的位置，单位为米
      "left_hand_pos": [0.0, 0.0, 0.0],
      
      # 左手相对于参考坐标系的姿态，四元数[x,y,z,w]
      "left_hand_quat": [0.0, 0.0, 0.0, 1.0],
      
      # 右手相对于参考坐标系的位置，单位为米
      "right_hand_pos": [0.0, 0.0, 0.0],
      
      # 右手相对于参考坐标系的姿态，四元数[x,y,z,w]
      "right_hand_quat": [0.0, 0.0, 0.0, 1.0]
  }
}
```

##### 3.4.14.2.2 响应：response_set_ub_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_ub_manip_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误, fail_invalid_cmd: 非法指令
  }
}
```

##### 3.4.14.2.3 消息推送：无

#### 3.4.14.3 获取移动操作位姿信息

##### 3.4.14.3.1 请求：request_get_ub_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_ub_manip_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
  }
}
```

##### 3.4.14.3.2 响应：response_get_ub_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_get_ub_manip_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    # 参考坐标系定义：
    # 原点：base_link坐标系
    # 方向：x方向对齐机器人正前方，y方向朝向机器人左侧，z方向竖直向上
    #
    # 参数定义：
    # 头相对于参考坐标系的位置，单位为米
    "head_pos": [0.0, 0.0, 0.0],
      
    # 头相对于参考坐标系的姿态，四元数[x,y,z,w]
    "head_quat": [0.0, 0.0, 0.0, 1.0],
    
    # 左手相对于参考坐标系的位置，单位为米
    "left_hand_pos": [0.0, 0.0, 0.0],
      
    # 左手相对于参考坐标系的姿态，四元数[x,y,z,w]
    "left_hand_quat": [0.0, 0.0, 0.0,1.0],
      
    # 右手相对于参考坐标系的位置，单位为米
    "right_hand_pos": [0.0, 0.0, 0.0],
      
    # 右手相对于参考坐标系的姿态，四元数[x,y,z,w]
    "right_hand_quat": [0.0, 0.0, 0.0,1.0],
    "result": "success"  # success: 成功, fail_motor: 电机错误, fail_invalid_cmd: 非法指令
  }
}
```

### 3.4.15 机器人原地操作

#### 3.4.15.1 进入原地操作模式

原地操作模式下，您可控制机器人的身体运动，但无法操控其行走功能。

##### 3.4.15.1.1 请求：request_set_wb_manip_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_wb_manip_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "mode": 0  # 0: 准备进入模式 1: 操作模式，开始跟踪末端位置 2: 准备退出模式
  }
}
```

##### 3.4.15.1.2 响应：response_set_wb_manip_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_wb_manip_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.4.15.1.3 消息推送：无

#### 3.4.15.2 原地操作控制

需要通过协议接口 `request_set_wb_manip_mode`，mode 为 1 进入原地操作模式下，功能才生效。

- **参考坐标系示意图：**
  - 位置 —— left_ankle_roll_link 与 right_ankle_roll_link 原点连线的中点
  - 姿态 —— yaw方向为 left_ankle_roll_link 与 right_ankle_roll_link 转向的中间值
  - 坐标轴定义：红色为x方向：由机器人双脚朝向决定；绿色为y方向：可根据右手坐标系规则确定；蓝色为z方向：竖直朝上。

|  |  |
| --- | --- |
| <img src="data:image/webp;base64,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" alt="图片" width="100" height="182" /> | <img src="data:image/webp;base64,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" alt="图片" width="108" height="176" /> |

##### 3.4.15.2.1 请求：request_set_wb_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_wb_manip_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 参考坐标系定义：
      # 原点：为左脚以及右脚的中心位置在地面上的投影（z=0)
      # 方向：x方向对齐机器人正前方，y方向朝向机器人左侧，z方向竖直向上
      #
      # 参数定义：
      # 左手相对于参考坐标系的位置，单位为米
      "left_hand_pos": [0.0, 0.3, 0.8],
      
      # 左手相对于参考坐标系的姿态，四元数[x,y,z,w]
      "left_hand_quat": [0.0, 0.0, 0.0, 1.0],
      
      # 右手相对于参考坐标系的位置，单位为米
      "right_hand_pos": [0.0, -0.3, 0.8],
      
      # 右手相对于参考坐标系的姿态，四元数[x,y,z,w]
      "right_hand_quat": [0.0, 0.0, 0.0, 1.0]
  }
}
```

##### 3.4.15.2.2 响应：response_set_wb_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_wb_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误, fail_invalid_cmd: 非法指令
  }
}
```

##### 3.4.15.2.3 消息推送：无

#### 3.4.15.3 获取原地操作位姿信息

##### 3.4.15.3.1 请求：request_get_wb_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_wb_manip_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
  }
}
```

##### 3.4.15.3.2 响应：response_get_wb_manip_ee_pose

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_get_wb_manip_ee_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    # 参考坐标系定义：
    # 原点：为左脚以及右脚的中心位置在地面上的投影（z=0)
    # 方向：x方向对齐机器人正前方，y方向朝向机器人左侧，z方向竖直向上
    #
    # 参数定义：
    # 左手相对于参考坐标系的位置，单位为米
    "left_hand_pos": [0.0, 0.0, 0.0],
      
    # 左手相对于参考坐标系的姿态，四元数[x,y,z,w]
    "left_hand_quat": [0.0, 0.0, 0.0, 1.0],
      
    # 右手相对于参考坐标系的位置，单位为米
    "right_hand_pos": [0.0, 0.0, 0.0],
      
    # 右手相对于参考坐标系的姿态，四元数[x,y,z,w]
    "right_hand_quat": [0.0, 0.0, 0.0, 1.0],
    "result": "success"  # success: 成功, fail_motor: 电机错误, fail_invalid_cmd: 非法指令
  }
}
```

##### 3.4.15.3.3 消息推送：无

### 3.4.16 双臂协同 Move 控制

#### 3.4.16.1 切换 Move 控制模式

##### 3.4.16.1.1 请求：request_set_move_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_move_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 0: 退出Move控制
      # 1: 移动Move模式
      # 2: 原地Move模式
      "mode": 0 
  }
}
```

##### 3.4.16.1.2 响应：response_set_move_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_move_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.4.16.1.3 消息推送：无

#### 3.4.16.2 MoveJ 控制指令

##### 3.4.16.2.1 请求：request_moveJ

```python
{
  "accid": "HU_D04_01_001",
  "title": "request_moveJ",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 各关节位置范围根据对应型号机器人URDF获取
      # 模型文件下载地址：https://github.com/limxdynamics/humanoid-description
      
      # 如您同时给出以下数据，则会控制双臂运动(目标位置，单位弧度)
      # 左臂关节顺序：  
      # - "left_shoulder_pitch_joint"
      # - "left_shoulder_roll_joint"
      # - "left_shoulder_yaw_joint"
      # - "left_elbow_joint"
      # - "left_wrist_yaw_joint"
      # - "left_wrist_pitch_joint"
      # - "left_wrist_roll_joint"
      "left": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
      
      # 右臂关节顺序：  
      # - "right_shoulder_pitch_joint"
      # - "right_shoulder_roll_joint"
      # - "right_shoulder_yaw_joint"
      # - "right_elbow_joint"
      # - "right_wrist_yaw_joint"
      # - "right_wrist_pitch_joint"
      # - "right_wrist_roll_joint"
      "right": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
      
      # 仅在原地MoveJ可控，如您同时给出以下数据，则会控制躯干姿态
      "torso_height": 0,  # 调整身高比例值，取值范围[-1, 1]
      "torso_pitch": 0,   # Pitch方向运动比例值，取值范围[-1, 1]
      "torso_roll": 0,    # Roll方向运动比例值，取值范围[-1, 1]
      "torso_yaw": 0,     # Yaw方向运动比例值，取值范围[-1, 1]
      
      # 如您同时给出以下数据，则会控制头运动
      "head_pitch": 0.0,  # pitch 关节的目标位置，单位为弧度
      "head_yaw": 0.0,    # yaw 关节的目标位置，单位为弧度
      
      "speed": 0.2  # 运动速度，取值范围为 0 到 0.5 弧度 / 秒，控制双臂运动的快慢
  }
}
```

##### 3.4.16.2.2 响应：response_moveJ

```python
{
  "accid": "HU_D04_01_001",
  "title": "response_moveJ",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.4.16.2.3 消息推送：notify_moveJ

执行完成或失败，主动推送此消息。

```python
{
  "accid": "HU_D04_01_001",
  "title": "notify_moveJ",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 执行完成， fail_motor: 电机错误， fail_invalid_speed: 非法速度值
  }
}
```

#### 3.4.16.3 MoveP 控制指令

- **参考坐标系示意图：**
  - 位置 —— waist_pitch_link 的原点
  - 坐标轴定义：红色为x方向：机器人前进方向；绿色为y方向：正方向向左；蓝色为z方向：竖直朝上

|  |  |
| --- | --- |
| <img src="data:image/webp;base64,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" alt="图片" width="92" height="183" /> | <img src="data:image/webp;base64,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" alt="图片" width="113" height="172" /> |

##### 3.4.16.3.1 请求：request_moveP

```python
{
  "accid": "HU_D04_01_001",
  "title": "request_moveP",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 如您同时给出以下数据，则会控制双臂运动
      "left_position": [0.0, 0.0, 0.0], # 表示左臂末端要移动到的目标位置，单位为米，顺序为 x, y, z
      "left_quat": [0.0, 0.0, 0.0, 1.0], # 用四元数（x, y, z, w）表示左臂末端的目标姿态
      "right_position": [0.0, 0.0, 0.0], # 表示右臂末端要移动到的目标位置，单位为米，顺序为 x, y, z
      "right_quat": [0.0, 0.0, 0.0, 1.0], # 用四元数（x, y, z, w）表示右臂末端的目标姿态
      
      # 仅在原地MoveP可控，如您同时给出以下数据，则会控制躯干姿态
      "torso_height": 0,  # 调整身高比例值，取值范围[-1, 1]
      "torso_pitch": 0,   # Pitch方向运动比例值，取值范围[-1, 1]
      "torso_roll": 0,    # Roll方向运动比例值，取值范围[-1, 1]
      "torso_yaw": 0,     # Yaw方向运动比例值，取值范围[-1, 1]
      
      # 如您同时给出以下数据，则会控制头运动
      "head_pitch": 0.0,  # pitch 关节的目标位置，单位为弧度
      "head_yaw": 0.0,    # yaw 关节的目标位置，单位为弧度
      
      "speed": 0.2  # 运动速度，取值范围为 0 到 0.5 弧度 / 秒，控制双臂运动的快慢
  }
}
```

##### 3.4.16.3.2 响应：response_moveP

```python
{
  "accid": "HU_D04_01_001",
  "title": "response_moveP",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.4.16.3.3 消息推送：notify_moveP

执行完成或失败，主动推送此消息。

```python
{
  "accid": "HU_D04_01_001",
  "title": "notify_moveP",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 执行完成， fail_motor: 电机错误， fail_invalid_speed: 非法速度值
  }
}
```

#### 3.4.16.4 获取双臂末端位姿

##### 3.4.16.4.1 请求：request_get_move_pose

通过此接口获取机器人双臂的末端位姿信息。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_move_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.16.4.2 响应：response_get_move_pose

接收到请求后，返回双臂当前位姿的相关信息。

```
{
  "accid": "HU_D04_01_001",
  "title": "response_get_move_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "timestamp": 1672373633989, # 表示数据时戳，单位为毫秒
      "left_position": [0.0, 0.0, 0.0], # 表示左臂末端的位置，单位为米，顺序为 x, y, z
      "left_quat": [0.0, 0.0, 0.0, 1.0], # 表示左臂末端的姿态，以四元数表示，顺序为 x, y, z, w
      "right_position": [0.0, 0.0, 0.0], # 表示右臂末端的位置，单位为米，顺序为 x, y, z
      "right_quat": [0.0, 0.0, 0.0, 1.0], # 表示右臂末端的姿态，以四元数表示，顺序为 x, y, z, w
      "result": "success"  # fail_not_data
  }
}
```

### 3.4.17 双臂协同 Servo 控制

#### 3.4.17.1 切换 Servo 控制模式

##### 3.4.17.1.1 请求：request_set_servo_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_servo_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 0: 退出Servo控制
      # 1: 移动Servo模式
      # 2: 原地Servo模式
      "mode": 0
  }
}
```

##### 3.4.17.1.2 响应：response_set_servo_mode

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_servo_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.4.17.1.3 消息推送：无

#### 3.4.17.2 ServoJ 控制指令

##### 3.4.17.2.1 请求：request_servoJ

- 推荐在实时系统中按控制频率 >= 500Hz 要求来控制机械臂运动，以保证控制效果和稳定性。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_servoJ",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 各关节位置范围根据对应型号机器人URDF获取
      # 模型文件下载地址：https://github.com/limxdynamics/humanoid-description
      
      # 如您同时给出以下数据，则会控制双臂运动(目标位置，单位弧度)
      # 左臂关节顺序：  
      # - "left_shoulder_pitch_joint"
      # - "left_shoulder_roll_joint"
      # - "left_shoulder_yaw_joint"
      # - "left_elbow_joint"
      # - "left_wrist_yaw_joint"
      # - "left_wrist_pitch_joint"
      # - "left_wrist_roll_joint"
      "left": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
      
      # 右臂关节顺序：  
      # - "right_shoulder_pitch_joint"
      # - "right_shoulder_roll_joint"
      # - "right_shoulder_yaw_joint"
      # - "right_elbow_joint"
      # - "right_wrist_yaw_joint"
      # - "right_wrist_pitch_joint"
      # - "right_wrist_roll_joint"
      "right": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
      
      # 仅在原地ServoJ可控，如您同时给出以下数据，则会控制躯干姿态
      "torso_height": 0,  # 调整身高比例值，取值范围[-1, 1]
      "torso_pitch": 0,   # Pitch方向运动比例值，取值范围[-1, 1]
      "torso_roll": 0,    # Roll方向运动比例值，取值范围[-1, 1]
      "torso_yaw": 0,     # Yaw方向运动比例值，取值范围[-1, 1]
      
      # 如您同时给出以下数据，则会控制头运动
      "head_yaw": 0.0,    # yaw 关节的目标位置，单位为弧度
      "head_pitch": 0.0  # picth 关节的目标位置，单位为弧度
  }
}
```

##### 3.4.17.2.2 响应：无

##### 3.4.17.2.3 消息推送：notify_servoJ

当 ServoJ 控制操作执行失败时，服务器会主动推送此消息，告知客户端失败原因。

```json
{
  "accid": "HU_D04_01_001",
  "title": "notify_servoJ",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "fail_invalid_cmd"  # fail_invalid_cmd: 非法指令， fail_motor: 电机错误
  }
}
```

#### 3.4.17.3 ServoP 控制指令

- **参考坐标系示意图：**
  - 位置 —— waist_pitch_link 的原点
  - 坐标轴定义：红色为x方向：机器人前进方向；绿色为y方向：正方向向左；蓝色为z方向：竖直朝上。

<div style="display: flex; align-items: flex-start; gap: 12px;">
<img src="data:image/webp;base64,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" alt="图片" width="92" height="183" />
<img src="data:image/webp;base64,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" alt="图片" width="113" height="172" />
</div>

##### 3.4.17.3.1 请求：request_servoP

- 推荐在实时系统中按控制频率 >= 500Hz 要求来控制机械臂运动，以保证控制效果和稳定性。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_servoP",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 如您同时给出以下数据，则会控制双臂运动
      "left_position": [0.0, 0.0, 0.0], # 表示左臂末端的目标位置，单位为米，顺序为 x，y, z
      "left_quat": [0.0, 0.0, 0.0, 1.0], # 以四元数（x, y, z, w）形式表示左臂末端的目标姿态
      "right_position": [0.0, 0.0, 0.0], # 表示右臂末端的目标位置，单位为米，顺序为 x，y, z
      "right_quat": [0.0, 0.0, 0.0, 1.0] # 以四元数（x, y, z, w）形式表示右臂末端的目标姿态
      
      # 仅在原地ServoP可控，如您同时给出以下数据，则会控制躯干姿态
      "torso_height": 0,  # 调整身高比例值，取值范围[-1, 1]
      "torso_pitch": 0,   # Pitch方向运动比例值，取值范围[-1, 1]
      "torso_roll": 0,    # Roll方向运动比例值，取值范围[-1, 1]
      "torso_yaw": 0,     # Yaw方向运动比例值，取值范围[-1, 1]
      
      # 如您同时给出以下数据，则会控制头运动
      "head_yaw": 0.0,    # yaw 关节的目标位置，单位为弧度
      "head_pitch": 0.0  # picth 关节的目标位置，单位为弧度
  }
}
```

##### 3.4.17.3.2 响应：无

##### 3.4.17.3.3 消息推送：notify_servoP

当 ServoP 控制操作执行失败时，服务器会主动推送此消息，告知客户端失败原因。

```json
{
  "accid": "HU_D04_01_001",
  "title": "notify_servoP",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "fail_invalid_cmd"  # fail_invalid_cmd: 非法指令， fail_motor: 电机错误
  }
}
```

#### 3.4.17.4 获取双臂末端位姿

##### 3.4.17.4.1 请求：request_get_servo_pose

通过此接口获取机器人双臂的末端位姿信息。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_servo_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 3.4.17.4.2 响应：response_get_servo_pose

接收到请求后，返回双臂当前位姿的相关信息。

```
{
  "accid": "HU_D04_01_001",
  "title": "response_get_servo_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "timestamp": 1672373633989, # 表示数据时戳，单位为毫秒
      "left_position": [0.0, 0.0, 0.0], # 表示左臂末端的位置，单位为米，顺序为 x, y, z
      "left_quat": [0.0, 0.0, 0.0, 1.0], # 表示左臂末端的姿态，以四元数表示，顺序为 x, y, z, w
      "right_position": [0.0, 0.0, 0.0], # 表示右臂末端的位置，单位为米，顺序为 x, y, z
      "right_quat": [0.0, 0.0, 0.0, 1.0], # 表示右臂末端的姿态，以四元数表示，顺序为 x, y, z, w
      "result": "success"  # fail_not_data
  }
}
```

##### 3.4.17.4.3 消息推送：无

### 3.4.18 机器人关节状态

#### 3.4.18.1 请求：request_get_joint_state

此请求用于获取机器人的各个关节状态。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_joint_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.4.18.2 响应：response_get_joint_state

接收到请求后，返回机器人各个关节当前状态。

```
{
  "accid": "HU_D04_01_001",
  "title": "response_get_joint_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "names": [], # 各个关节的名称
      "q": [],     # 各个关节的位置
      "dq": [],    # 各个关节的速度
      "tau": [],   # 各个关节的扭矩
      "result": "success"  # fail_not_data
  }
}
```

#### 3.4.18.3 消息推送：无

### 3.4.19 获取 IMU 数据

#### 3.4.19.1 请求：request_get_imu_data

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_imu_data",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.4.19.2 响应：response_get_imu_data

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_get_imu_data",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"， # fail_no_data
      "euler": [0.0, 0.0, 0.0],     // 欧拉角 [roll, pitch, yaw] in degrees
      "acc": [0.0, 0.0, 0.0],       // 加速度 [x, y, z] in m/s²
      "gyro": [0.0, 0.0, 0.0],      // 陀螺仪角速度 [x, y, z] in rad/s
      "quat": [0.0, 0.0, 0.0, 0.0]  // 四元数 [w, x, y, z]
  }
}
```

#### 3.4.19.3 消息推送：无

## 3.5 灵巧手及夹爪协议接口

### 3.5.1 逐际二指夹爪

#### 3.5.1.1 夹爪控制指令

##### 3.5.1.1.1 请求：request_set_limx_2fclaw_cmd

此协议控制夹爪的抓取动作。

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_limx_2fclaw_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 如您同时给出以下数据，则会控制左夹爪运动
      "left_opening": 50,  # 开口度，0-100，无量纲（0对应最小闭合，100对应张开到最大）
      "left_speed": 50,    # 夹爪速度，0~100 无量纲（数值越大速度越快）
      "left_force": 50,   #力，夹爪夹持力，0~100 无单位（数值越大力越大）
      
      # 如您同时给出以下数据，则会控制右夹爪运动
      "right_opening": 50,  # 开口度，0-100，无量纲（0对应最小闭合，100对应张开到最大）
      "right_speed": 50,    # 夹爪速度，0~100 无量纲（数值越大速度越快）
      "right_force": 50,   #力，夹爪夹持力，0~100 无单位（数值越大力越大）
  }
}
```

##### 3.5.1.1.2 响应：response_set_limx_2fclaw_cmd

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_limx_2fclaw_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.5.1.1.3 消息推送：无

#### 3.5.1.2 获取夹爪状态信息

##### 3.5.1.2.1 请求：request_get_limx_2fclaw_state

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_limx_2fclaw_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
  }
}
```

##### 3.5.1.2.2 响应：response_get_limx_2fclaw_state

返回夹爪状态信息

##### 3.5.1.2.3 消息推送：无

### 3.5.2 逐际三指夹爪

#### 3.5.2.1 夹爪控制指令

##### 3.5.2.1.1 请求：request_set_limx_3fclaw_cmd

此协议控制夹爪的抓取动作。

##### 3.5.2.1.2 响应：response_set_limx_3fclaw_cmd

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_limx_3fclaw_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.5.2.1.3 消息推送：无

#### 3.5.2.2 获取夹爪状态信息

##### 3.5.2.2.1 请求：request_get_limx_3fclaw_state

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_limx_3fclaw_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
  }
}
```

##### 3.5.2.2.2 响应：response_get_limx_3fclaw_state

返回夹爪状态信息

##### 3.5.2.2.3 消息推送：无

### 3.5.3 因时二指夹爪

#### 3.5.3.1 夹爪控制指令

##### 3.5.3.1.1 请求：request_set_claw_cmd

此协议控制夹爪的抓取动作。

##### 3.5.3.1.2 响应：response_set_claw_cmd

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_claw_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.5.3.1.3 消息推送：无

#### 3.5.3.2 获取夹爪状态信息

##### 3.5.3.2.1 请求：request_get_claw_state

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_claw_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
  }
}
```

##### 3.5.3.2.2 响应：response_get_claw_state

返回夹爪状态信息

##### 3.5.3.2.3 消息推送：无

### 3.5.4 强脑 1 代灵巧手

#### 3.5.4.1 灵巧手控制指令

##### 3.5.4.1.1 请求：request_set_brainco_hand_cmd

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_brainco_hand_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 如您给定以下数据，则会控制左手运动
      "left_thumb": 50,       # 左手大拇指弯曲角度，0-100，无量纲
      "left_thumb_aux": 50,   # 左手大拇指内收角度，0-100，无量纲
      "left_index": 50,       # 左手食指弯曲角度，0-100，无量纲
      "left_middle": 50,      # 左手中指弯曲角度，0-100，无量纲
      "left_ring": 50,        # 左手无名指弯曲角度，0-100，无量纲
      "left_pinky": 50,       # 左手小指弯曲角度，0-100，无量纲
      "left_mode": 3,         # 力量等级 1：小 2：中 3：大。默认值为：2
      
      # 如您给定以下数据，则会控制右手运动
      "right_thumb": 50,       # 右手大拇指弯曲角度，0-100，无量纲
      "right_thumb_aux": 50,   # 右手大拇指内收角度，0-100，无量纲
      "right_index": 50,       # 右手食指弯曲角度，0-100，无量纲
      "right_middle": 50,      # 右手中指弯曲角度，0-100，无量纲
      "right_ring": 50,        # 右手无名指弯曲角度，0-100，无量纲
      "right_pinky": 50,       # 右手小指弯曲角度，0-100，无量纲
      "right_mode": 3          # 力量等级 1：小 2：中 3：大。默认值为：2
  }
}
```

##### 3.5.4.1.2 响应：response_set_brainco_hand_cmd

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_brainco_hand_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.5.4.1.3 消息推送：无

#### 3.5.4.2 获取灵巧手状态

##### 3.5.4.2.1 请求：request_get_brainco_hand_state

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_brainco_hand_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
  }
}
```

##### 3.5.4.2.2 响应：response_get_brainco_hand_state

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_get_brainco_hand_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "timestamp": 1672373633989, # 表示数据时戳，单位为毫秒
      "left_thumb": 50,       # 左手大拇指弯曲角度，0-100，无量纲
      "left_thumb_aux": 50,   # 左手大拇指内收角度，0-100，无量纲
      "left_index": 50,       # 左手食指弯曲角度，0-100，无量纲
      "left_middle": 50,      # 左手中指弯曲角度，0-100，无量纲
      "left_ring": 50,        # 左手无名指弯曲角度，0-100，无量纲
      "left_pinky": 50,       # 左手小指弯曲角度，0-100，无量纲
      
      "right_thumb": 50,       # 右手大拇指弯曲角度，0-100，无量纲
      "right_thumb_aux": 50,   # 右手大拇指内收角度，0-100，无量纲
      "right_index": 50,       # 右手食指弯曲角度，0-100，无量纲
      "right_middle": 50,      # 右手中指弯曲角度，0-100，无量纲
      "right_ring": 50,        # 右手无名指弯曲角度，0-100，无量纲
      "right_pinky": 50        # 右手小指弯曲角度，0-100，无量纲
      "result": "success"  # success: 成功, fail_motor: 电机错误
  }
}
```

##### 3.5.4.2.3 消息推送：无

### 3.5.5 强脑 2 代灵巧手

#### 3.5.5.1 灵巧手控制指令

##### 3.5.5.1.1 请求：request_set_brainco2_hand_cmd

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_set_brainco2_hand_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 左手：
      # 索引从0-5分别对应：拇指尖、拇指根、食指、中指、无名指、小指
      # left_mode: 控制模式
      #            0：退出控制
      #            1：位置时间模式, 必须指定 left_pos、left_time 的值
      #            2：位置速度模式, 必须指定 left_pos、left_vel 的值
      #            3：力控模式, 必须指定 left_current 的值
      # left_pos: 每个手指的目标位置, 单位为rad
      #           范围分别为0-1.0297、0-1.5707、0-1.4137、0-1.4137、0-1.4137、0-1.4137
      # left_vel: 每个手指的目标速度, 单位为rad/s
      #           范围分别为0-2.5367、0-2.6180、0-2.2689、0-2.2689、0-2.2689、0-2.2689
      # left_current: 每个手指的目标电流, 单位为mA, 范围为±1000mA
      # left_time: 每个手指的控制时间, 单位为ms, 范围为1-2000ms
      
      "left_mode": 1,
      "left_pos": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "left_vel": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "left_current": [500, 500, 500, 500, 500, 500],
      "left_time": [1000, 1000, 1000, 1000, 1000, 1000],
      
      # 右手：
      # 索引从0-5分别对应：拇指尖、拇指根、食指、中指、无名指、小指
      # right_mode: 控制模式
      #            0：退出控制
      #            1：位置时间模式, 必须指定 right_pos、right_time 的值
      #            2：位置速度模式, 必须指定 right_pos、right_vel 的值
      #            3：力控模式, 必须指定 right_current 的值
      # right_pos: 每个手指的目标位置, 单位为rad
      #           范围分别为0-1.0297、0-1.5707、0-1.4137、0-1.4137、0-1.4137、0-1.4137
      # right_vel: 每个手指的目标速度, 单位为rad/s
      #           范围分别为0-2.5367、0-2.6180、0-2.2689、0-2.2689、0-2.2689、0-2.2689
      # right_current: 每个手指的目标电流, 单位为mA, 范围为±1000mA
      # right_time: 每个手指的控制时间, 单位为ms, 范围为1-2000ms
      
      "right_mode": 1,
      "right_pos": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "right_vel": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "right_current": [500, 500, 500, 500, 500, 500],
      "right_time": [1000, 1000, 1000, 1000, 1000, 1000]
  }
}
```

##### 3.5.5.1.2 响应：response_set_brainco2_hand_cmd

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_set_brainco2_hand_cmd",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"  # success: 成功, fail_motor: 电机错误, fail_invalid_cmd: 非法指令
  }
}
```

##### 3.5.5.1.3 消息推送：无

#### 3.5.5.2 获取灵巧手状态

##### 3.5.5.2.1 请求：request_get_brainco2_hand_state

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_get_brainco2_hand_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
  }
}
```

##### 3.5.5.2.2 响应：response_get_brainco2_hand_state

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_get_brainco2_hand_state",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "timestamp": 1672373633989,
      "left_mode": 1,
      "left_pos": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "left_vel": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "left_current": [500, 500, 500, 500, 500, 500],
      "left_time": [1000, 1000, 1000, 1000, 1000, 1000],
      "right_mode": 1,
      "right_pos": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "right_vel": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
      "right_current": [500, 500, 500, 500, 500, 500],
      "right_time": [1000, 1000, 1000, 1000, 1000, 1000]
  }
}
```

##### 3.5.5.2.3 消息推送：无

## 3.6 音频设备接口

### 3.6.1 概述

机器人提供音频设备相关的 WebSocket API，支持麦克风采集、喇叭播放、唤醒词检测和音量控制等功能。

音频服务支持以下核心能力：

- 音频采集：实时音频流推送和一次性录音
- 音频播放：支持 PCM 原始数据播放和音频文件播放（本地文件或远程 URL，支持 PCM/WAV/MP3）
- 唤醒词检测：支持语音唤醒词检测，检测到唤醒词时主动推送事件
- 音量控制：全局播放音量调节

### 3.6.2 音频流推送控制

音频流推送开关。开启后，系统通过 `notify_audio_capture` 将 PCM 音频数据持续推送至客户端；关闭后停止推送。

#### 3.6.2.1 请求：request_audio_capture

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_capture",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "streaming": 1  # 1: 开启推送, 0: 关闭推送
  }
}
```

#### 3.6.2.2 响应：response_audio_capture

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_capture",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功
  }
}
```

#### 3.6.2.3 消息推送：notify_audio_capture

开启音频流推送后，系统会持续下发采集到的 PCM 音频数据片段。

```json
{
  "accid": "HU_D04_01_001",
  "title": "notify_audio_capture",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "sample_rate": 16000,  # 采样率，单位 Hz
      "channels": 1,         # 声道数
      "samples": [...]       # PCM 数据，int16 数组
  }
}
```

#### 3.6.2.4 代码示例：audio_capture_ws.py

audio_capture_ws.py                          # 默认录制 5 秒

audio_capture_ws.py -d 10 -o test.wav        # 录制 10 秒，保存到 test.wav

audio_capture_ws.py --host 10.192.1.2        # 指定 IP

```python
#!/usr/bin/env python3
"""
audio_capture_ws.py - Real-time audio capture test tool (WebSocket)

Captures audio in real-time via WebSocket and saves to WAV file.
   -> request_audio_capture (streaming:1 start)
   -> listen notify_audio_capture for PCM data
   -> request_audio_capture (streaming:0 stop)
   -> save WAV

Usage:
    audio_capture_ws.py                          # Record 5 seconds
    audio_capture_ws.py -d 10 -o test.wav        # Record 10s, save to test.wav
    audio_capture_ws.py --host 10.192.1.2        # Specify robot IP

Dependencies:
    pip install websocket-client numpy
"""

import sys
import json
import uuid
import struct
import math
import time
import argparse
import threading
import numpy as np
import websocket

ACCID = None
TAG = "AudioCapture"

# Pending request events: guid -> (threading.Event, holder_dict)
_pending = {}
_pending_lock = threading.Lock()

# Notify callbacks: title -> callback(data_dict)
_notify_cbs = {}

ws_client = None
_accid_event = threading.Event()


def generate_guid():
    return str(uuid.uuid4())


def send_request(title, data=None, timeout=10):
    global ACCID
    guid = generate_guid()
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": guid,
        "data": data or {},
    }
    evt = threading.Event()
    holder = {"resp": None}
    with _pending_lock:
        _pending[guid] = (evt, holder)

    ws_client.send(json.dumps(msg))

    if not evt.wait(timeout):
        with _pending_lock:
            _pending.pop(guid, None)
        raise TimeoutError("Request %s timed out after %ds" % (title, timeout))

    with _pending_lock:
        _pending.pop(guid, None)
    return holder["resp"] or {}


def on_ws_message(ws, message):
    global ACCID
    root = json.loads(message)
    title = root.get("title", "")
    if root.get("accid"):
        ACCID = root.get("accid")
        _accid_event.set()

    if title.startswith("response_"):
        guid = root.get("guid", "")
        with _pending_lock:
            entry = _pending.get(guid)
        if entry:
            evt, holder = entry
            holder["resp"] = root.get("data", {})
            evt.set()
    elif title.startswith("notify_"):
        if title == "notify_audio_capture":
            data = root.get("data", {})
            n = len(data.get("samples", []))
        cb = _notify_cbs.get(title)
        if cb:
            try:
                cb(root.get("data", {}))
            except Exception:
                pass


def on_ws_open(ws):
    print("[%s] WebSocket connected." % TAG)


def on_ws_close(ws, code, msg):
    print("[%s] WebSocket closed." % TAG)


# ============================================================================
# WAV writer
# ============================================================================
def write_wav(filepath, pcm_data, sample_rate, channels, bits_per_sample=16):
    num_samples = len(pcm_data)
    data_bytes = pcm_data.astype(np.int16).tobytes()
    data_size = len(data_bytes)
    byte_rate = sample_rate * channels * (bits_per_sample // 8)
    block_align = channels * (bits_per_sample // 8)

    with open(filepath, "wb") as f:
        f.write(b"RIFF")
        f.write(struct.pack("<I", 4 + (8 + 16) + (8 + data_size)))
        f.write(b"WAVE")
        f.write(b"fmt ")
        f.write(struct.pack("<I", 16))
        f.write(struct.pack("<HHIIHH", 1, channels, sample_rate,
                            byte_rate, block_align, bits_per_sample))
        f.write(b"data")
        f.write(struct.pack("<I", data_size))
        f.write(data_bytes)

    duration = num_samples / (sample_rate * channels)
    print("[%s] Saved %s (%d samples, %.1fs)" % (TAG, filepath, num_samples, duration))


# ============================================================================
# Capture logic
# ============================================================================
class AudioCaptureTest:
    def __init__(self, output, duration):
        self.output = output
        self.duration = duration
        self.lock = threading.Lock()
        self.pcm_buffer = np.array([], dtype=np.int16)
        self.sample_rate = 16000
        self.channels = 1
        self.done = False
        self.last_rms_db = -96

    def on_capture(self, data):
        if self.done:
            return
        try:
            self.sample_rate = data.get("sample_rate", 16000)
            self.channels = data.get("channels", 1)
            samples = np.array(data.get("samples", []), dtype=np.int16)
            if len(samples) == 0:
                return

            rms = np.sqrt(np.mean(samples.astype(np.float64) ** 2))
            self.last_rms_db = int(20 * math.log10(rms / 32768.0)) if rms > 0 else -96

            target = int(self.duration * self.sample_rate * self.channels)
            with self.lock:
                remaining = target - len(self.pcm_buffer)
                to_copy = min(len(samples), remaining)
                self.pcm_buffer = np.concatenate([self.pcm_buffer, samples[:to_copy]])
                if len(self.pcm_buffer) >= target:
                    self.done = True
        except Exception as e:
            print("\n[%s] Error in callback: %s" % (TAG, e))

    def run(self):
        print("[%s] Config:" % TAG)
        print("  Output:   %s" % self.output)
        print("  Duration: %ds" % self.duration)
        print()

        _notify_cbs["notify_audio_capture"] = self.on_capture

        print("[%s] Enabling capture control ..." % TAG)

        print("[%s] Starting capture stream ..." % TAG)
        resp = send_request("request_audio_capture", {"streaming": 1})
        print("[%s] capture stream: %s" % (TAG, resp.get("result", "?")))
        print()

        print("[%s] Recording ..." % TAG)
        bar_width = 30
        try:
            while not self.done:
                time.sleep(0.05)
                with self.lock:
                    current = len(self.pcm_buffer)
                target = int(self.duration * self.sample_rate * self.channels)
                elapsed = current / max(self.sample_rate * self.channels, 1)
                filled = min(int(bar_width * current / max(target, 1)), bar_width)
                bar = "#" * filled + "-" * (bar_width - filled)
                sys.stdout.write("\r  [%s] %.1f/%ds  RMS: %d dB   "
                                 % (bar, elapsed, self.duration, self.last_rms_db))
                sys.stdout.flush()
        except KeyboardInterrupt:
            print("\n[%s] Interrupted by user." % TAG)

        print()

        send_request("request_audio_capture", {"streaming": 0})
        _notify_cbs.pop("notify_audio_capture", None)

        with self.lock:
            collected = len(self.pcm_buffer)
        if collected > 0:
            write_wav(self.output, self.pcm_buffer, self.sample_rate, self.channels)
        else:
            print("[%s] No audio data received!" % TAG)

        print("[%s] Done." % TAG)


def main():
    global ws_client

    parser = argparse.ArgumentParser(description="Audio Capture Test Tool (WebSocket)")
    parser.add_argument("-o", "--output", default="capture_test.wav",
                        help="Output WAV file path (default: capture_test.wav)")
    parser.add_argument("-d", "--duration", type=int, default=5,
                        help="Recording duration in seconds (default: 5)")
    parser.add_argument("--host", default="10.192.1.2",
                        help="Robot IP address (default: 10.192.1.2)")
    parser.add_argument("--port", type=int, default=5000,
                        help="WebSocket port (default: 5000)")
    args = parser.parse_args()

    print("[%s] ==========================================" % TAG)
    print("[%s]  Audio Capture (WebSocket)" % TAG)
    print("[%s] ==========================================" % TAG)

    test = AudioCaptureTest(args.output, args.duration)
    ready = threading.Event()

    def _on_open(ws):
        on_ws_open(ws)
        ready.set()

    ws_client = websocket.WebSocketApp(
        "ws://%s:%d" % (args.host, args.port),
        on_open=_on_open,
        on_message=on_ws_message,
        on_close=on_ws_close,
    )

    ws_thread = threading.Thread(target=ws_client.run_forever, daemon=True)
    ws_thread.start()

    print("[%s] Connecting to %s:%d ..." % (TAG, args.host, args.port))
    if not ready.wait(timeout=10):
        print("[%s] Connection timeout!" % TAG)
        return

    print("[%s] Waiting for ACCID ..." % TAG)
    if not _accid_event.wait(timeout=10):
        print("[%s] ACCID not received, timeout!" % TAG)
        return
    print("[%s] ACCID: %s" % (TAG, ACCID))

    try:
        test.run()
    finally:
        ws_client.close()


if __name__ == "__main__":
    main()
```

### 3.6.3 一次性录音

一次性录音功能。系统在指定时长内录制音频，录制完成后将完整 PCM 数据通过响应一次性返回。

#### 3.6.3.1 请求：request_audio_capture_record

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_capture_record",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "duration": 5.0  # 录音时长，单位秒
  }
}
```

#### 3.6.3.2 响应：response_audio_capture_record

录制完成后返回完整的 PCM 音频数据。

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_capture_record",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success",    # success: 成功
      "sample_rate": 16000,   # 采样率，单位 Hz
      "channels": 1,          # 声道数
      "samples": [...]        # PCM 数据，int16 数组
  }
}
```

#### 3.6.3.3 消息推送：无

#### 3.6.3.4 代码示例：audio_capture_record_ws.py

audio_capture_record_ws.py                    # 录制 5 秒

audio_capture_record_ws.py -d 10              # 录制 10 秒

audio_capture_record_ws.py -d 3 -o test.wav   # 录制 3 秒，保存到 test.wav

```python
#!/usr/bin/env python3
"""
audio_capture_record_ws.py - One-shot audio capture record test tool (WebSocket)

Requests a one-shot recording via request_audio_capture_record,
receives PCM data in the response and saves to WAV file.

Usage:
    audio_capture_record_ws.py                    # Record 5 seconds
    audio_capture_record_ws.py -d 10              # Record 10 seconds
    audio_capture_record_ws.py -d 3 -o test.wav   # Record 3s, save to test.wav
    audio_capture_record_ws.py --host 10.192.1.2

Dependencies:
    pip install websocket-client
"""

import json
import uuid
import struct
import time
import argparse
import threading
import websocket

ACCID = None
TAG = "AudioCaptureRecord"

_pending = {}
_pending_lock = threading.Lock()

ws_client = None
_accid_event = threading.Event()


def generate_guid():
    return str(uuid.uuid4())


def send_request(title, data=None, timeout=10):
    global ACCID
    guid = generate_guid()
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": guid,
        "data": data or {},
    }
    evt = threading.Event()
    holder = {"resp": None}
    with _pending_lock:
        _pending[guid] = (evt, holder)

    ws_client.send(json.dumps(msg))

    if not evt.wait(timeout):
        with _pending_lock:
            _pending.pop(guid, None)
        raise TimeoutError("Request %s timed out after %ds" % (title, timeout))

    with _pending_lock:
        _pending.pop(guid, None)
    return holder["resp"] or {}


def on_ws_message(ws, message):
    global ACCID
    root = json.loads(message)
    title = root.get("title", "")
    if root.get("accid"):
        ACCID = root.get("accid")
        _accid_event.set()

    if title.startswith("response_"):
        guid = root.get("guid", "")
        with _pending_lock:
            entry = _pending.get(guid)
        if entry:
            evt, holder = entry
            holder["resp"] = root.get("data", {})
            evt.set()


def on_ws_open(ws):
    print("[%s] WebSocket connected." % TAG)


def on_ws_close(ws, code, msg):
    print("[%s] WebSocket closed." % TAG)


# ============================================================================
# WAV writer
# ============================================================================
def write_wav(filepath, pcm_bytes, sample_rate, channels, bits_per_sample=16):
    block_align = channels * (bits_per_sample // 8)
    byte_rate = sample_rate * block_align
    data_size = len(pcm_bytes)
    file_size = 4 + (8 + 16) + (8 + data_size)

    with open(filepath, 'wb') as f:
        f.write(b'RIFF')
        f.write(struct.pack('<I', file_size))
        f.write(b'WAVE')
        f.write(b'fmt ')
        f.write(struct.pack('<I', 16))
        f.write(struct.pack('<H', 1))
        f.write(struct.pack('<H', channels))
        f.write(struct.pack('<I', sample_rate))
        f.write(struct.pack('<I', byte_rate))
        f.write(struct.pack('<H', block_align))
        f.write(struct.pack('<H', bits_per_sample))
        f.write(b'data')
        f.write(struct.pack('<I', data_size))
        f.write(pcm_bytes)


# ============================================================================
# Capture record logic
# ============================================================================
def capture_record(duration, output_path):
    print("[%s] Requesting capture_record (duration=%.1fs) ..." % (TAG, duration))

    timeout = int(duration + 15)
    resp = send_request("request_audio_capture_record",
                        {"duration": duration}, timeout=timeout)

    result = resp.get("result", "fail")
    if result != "success":
        print("[%s] FAIL: %s" % (TAG, resp.get("message", result)))
        return False

    sample_rate = int(resp.get("sample_rate", 16000))
    channels = int(resp.get("channels", 1))
    samples = resp.get("samples", [])

    pcm_bytes = b""
    for s in samples:
        pcm_bytes += struct.pack('<h', int(s))

    num_samples = len(samples)
    actual_dur = num_samples / max(sample_rate * channels, 1)

    print("[%s] OK: received %d samples (%.1fs, rate=%d, ch=%d)" % (
        TAG, num_samples, actual_dur, sample_rate, channels))

    write_wav(output_path, pcm_bytes, sample_rate, channels)
    print("[%s] Saved to: %s" % (TAG, output_path))
    return True


def main():
    global ws_client

    parser = argparse.ArgumentParser(description="Audio Capture Record Test Tool (WebSocket)")
    parser.add_argument("-d", "--duration", type=float, default=5.0,
                        help="Recording duration in seconds (default: 5.0)")
    parser.add_argument("-o", "--output", type=str, default="capture_record.wav",
                        help="Output WAV file path (default: capture_record.wav)")
    parser.add_argument("--host", default="10.192.1.2",
                        help="Robot IP address (default: 10.192.1.2)")
    parser.add_argument("--port", type=int, default=5000,
                        help="WebSocket port (default: 5000)")
    args = parser.parse_args()

    print("[%s] ==========================================" % TAG)
    print("[%s]  Audio Capture Record (WebSocket)" % TAG)
    print("[%s] ==========================================" % TAG)

    ready = threading.Event()

    def _on_open(ws):
        on_ws_open(ws)
        ready.set()

    ws_client = websocket.WebSocketApp(
        "ws://%s:%d" % (args.host, args.port),
        on_open=_on_open,
        on_message=on_ws_message,
        on_close=on_ws_close,
    )

    ws_thread = threading.Thread(target=ws_client.run_forever, daemon=True)
    ws_thread.start()

    print("[%s] Connecting to %s:%d ..." % (TAG, args.host, args.port))
    if not ready.wait(timeout=10):
        print("[%s] Connection timeout!" % TAG)
        return

    print("[%s] Waiting for ACCID ..." % TAG)
    if not _accid_event.wait(timeout=10):
        print("[%s] ACCID not received, timeout!" % TAG)
        return
    print("[%s] ACCID: %s" % (TAG, ACCID))

    try:
        capture_record(args.duration, args.output)
    finally:
        ws_client.close()

    print("[%s] Done." % TAG)


if __name__ == "__main__":
    main()
```

### 3.6.4 播放控制

喇叭播放全局开关。开启后初始化播放设备并开始消费播放队列；关闭时停止播放并清空队列。

系统启动后，喇叭播放默认为关闭状态，需要通过此接口手动开启。

#### 3.6.4.1 请求：request_audio_playback_control

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_playback_control",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "enable": 1  # 1: 开启播放, 0: 关闭播放
  }
}
```

#### 3.6.4.2 响应：response_audio_playback_control

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_playback_control",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功
  }
}
```

#### 3.6.4.3 消息推送：无

### 3.6.5 播放 PCM 数据

向播放队列发送 PCM 原始数据片段。支持分块连续发送，系统按顺序依次播放。

注意：调用前需先通过 `request_audio_playback_control` 开启播放功能。

#### 3.6.5.1 请求：request_audio_play_data

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_play_data",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "sample_rate": 16000,  # 采样率，单位 Hz
      "channels": 1,         # 声道数
      "samples": [...]       # PCM 数据，int16 数组
  }
}
```

#### 3.6.5.2 响应：response_audio_play_data

正常成功时不返回响应；仅失败时返回响应，客户端不应等待成功响应。

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_play_data",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "fail_no_samples"  # fail_no_samples: 缺少 PCM 数据
  }
}
```

#### 3.6.5.3 消息推送：无

#### 3.6.5.4 代码示例：audio_playback_ws.py

audio_playback_ws.py test.wav                # 播放 WAV 文件

audio_playback_ws.py --tone 1000 -d 3        # 播放 1000Hz 正弦波 3 秒

audio_playback_ws.py --sweep -d 5            # 播放 200~8000Hz 扫频 5 秒

audio_playback_ws.py --noise -d 3            # 播放白噪声 3 秒

audio_playback_ws.py --tone 1000 -v 50       # 50% 音量播放

audio_playback_ws.py --tone 1000 -a 0.1      # 10% 振幅播放 (喇叭保护)

```python
#!/usr/bin/env python3
"""
audio_playback_ws.py - Audio playback test tool (WebSocket)

Reads a WAV file or generates test tones, sends PCM data via
request_audio_play_data for playback, or request_audio_play_with_gesture
when --gesture is enabled. Gesture motion requires entering gesture mode with
request_audio_gesture_control first. Automatically calls
request_audio_playback_control to start/stop the playback queue.

Usage:
    audio_playback_ws.py test.wav                # Play WAV file
    audio_playback_ws.py --tone 1000 -d 3        # Play 1000Hz sine wave 3s
    audio_playback_ws.py --sweep -d 5            # Play 200~8000Hz sweep 5s
    audio_playback_ws.py --noise -d 3            # Play white noise 3s
    audio_playback_ws.py --host 10.192.1.2 --tone 440
    audio_playback_ws.py --tone 1000 -v 50       # Play at 50% volume
    audio_playback_ws.py --gesture-enter         # Enter gesture mode
    audio_playback_ws.py test.wav --gesture      # Play WAV file with gesture if mode entered
    audio_playback_ws.py --gesture-exit          # Exit gesture mode
    audio_playback_ws.py --start                  # Start playback queue
    audio_playback_ws.py --stop                   # Stop current playback
    audio_playback_ws.py --tone 1000 -a 0.1      # Play at 10% amplitude (speaker protection)

Dependencies:
    pip install websocket-client numpy
"""

import sys
import json
import uuid
import struct
import time
import argparse
import threading
import numpy as np
import websocket

ACCID = None
TAG = "AudioPlayback"
TAIL_SILENCE_MS = 1000

_pending = {}
_pending_lock = threading.Lock()

ws_client = None
_accid_event = threading.Event()


def generate_guid():
    return str(uuid.uuid4())


def send_request(title, data=None, timeout=10):
    global ACCID
    guid = generate_guid()
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": guid,
        "data": data or {},
    }
    evt = threading.Event()
    holder = {"resp": None}
    with _pending_lock:
        _pending[guid] = (evt, holder)

    ws_client.send(json.dumps(msg, separators=(",", ":")))

    if not evt.wait(timeout):
        with _pending_lock:
            _pending.pop(guid, None)
        raise TimeoutError("Request %s timed out after %ds" % (title, timeout))

    with _pending_lock:
        _pending.pop(guid, None)
    return holder["resp"] or {}


def send_request_no_response(title, data=None):
    global ACCID
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": generate_guid(),
        "data": data or {},
    }
    ws_client.send(json.dumps(msg, separators=(",", ":")))


def on_ws_message(ws, message):
    global ACCID
    root = json.loads(message)
    title = root.get("title", "")
    if root.get("accid"):
        ACCID = root.get("accid")
        _accid_event.set()

    if title.startswith("response_"):
        guid = root.get("guid", "")
        with _pending_lock:
            entry = _pending.get(guid)
        if entry:
            evt, holder = entry
            holder["resp"] = root.get("data", {})
            evt.set()


def on_ws_open(ws):
    print("[%s] WebSocket connected." % TAG)


def on_ws_close(ws, code, msg):
    print("[%s] WebSocket closed." % TAG)


# ============================================================================
# WAV file reader
# ============================================================================
def read_wav(filepath):
    PCM_GUID = b'\x01\x00\x00\x00\x00\x00\x10\x00\x80\x00\x00\xaa\x00\x38\x9b\x71'

    with open(filepath, "rb") as f:
        riff = f.read(4)
        if riff != b"RIFF":
            raise ValueError("Not a RIFF file")
        f.read(4)
        wave = f.read(4)
        if wave != b"WAVE":
            raise ValueError("Not a WAVE file")

        sample_rate = 0
        channels = 0
        bits_per_sample = 0
        pcm_data = None

        while True:
            chunk_header = f.read(8)
            if len(chunk_header) < 8:
                break
            chunk_id = chunk_header[:4]
            chunk_size = struct.unpack("<I", chunk_header[4:8])[0]

            if chunk_id == b"fmt ":
                fmt_data = f.read(chunk_size)
                audio_format = struct.unpack("<H", fmt_data[0:2])[0]
                channels = struct.unpack("<H", fmt_data[2:4])[0]
                sample_rate = struct.unpack("<I", fmt_data[4:8])[0]
                bits_per_sample = struct.unpack("<H", fmt_data[14:16])[0]

                if audio_format == 65534 and len(fmt_data) >= 40:
                    valid_bits = struct.unpack("<H", fmt_data[18:20])[0]
                    sub_format = fmt_data[24:40]
                    if sub_format == PCM_GUID:
                        audio_format = 1
                    if valid_bits > 0:
                        bits_per_sample = valid_bits

                if audio_format != 1:
                    raise ValueError("Unsupported audio format: %d" % audio_format)

            elif chunk_id == b"data":
                raw = f.read(chunk_size)
                if bits_per_sample == 16:
                    pcm_data = np.frombuffer(raw, dtype=np.int16)
                elif bits_per_sample == 8:
                    pcm_data = (np.frombuffer(raw, dtype=np.uint8).astype(np.int16) - 128) * 256
                elif bits_per_sample == 24:
                    num_samples = len(raw) // 3
                    pcm_data = np.zeros(num_samples, dtype=np.int16)
                    for i in range(num_samples):
                        b0, b1, b2 = raw[i*3], raw[i*3+1], raw[i*3+2]
                        sample32 = (b2 << 24) | (b1 << 16) | (b0 << 8)
                        if sample32 >= 0x80000000:
                            sample32 -= 0x100000000
                        pcm_data[i] = np.int16(sample32 >> 16)
                elif bits_per_sample == 32:
                    raw32 = np.frombuffer(raw, dtype=np.int32)
                    pcm_data = (raw32 >> 16).astype(np.int16)
                else:
                    raise ValueError("Unsupported bits_per_sample: %d" % bits_per_sample)
                break
            else:
                skip = chunk_size
                if skip & 1:
                    skip += 1
                f.seek(skip, 1)

    if pcm_data is None:
        raise ValueError("No data chunk found in WAV file")
    return pcm_data, sample_rate, channels


# ============================================================================
# Test tone generators
# ============================================================================
def generate_tone(freq, duration, sample_rate, channels, amplitude=0.2):
    num_samples = int(duration * sample_rate)
    t = np.arange(num_samples, dtype=np.float64) / sample_rate
    mono = (amplitude * 32767 * np.sin(2 * np.pi * freq * t)).astype(np.int16)
    if channels > 1:
        pcm = np.zeros(num_samples * channels, dtype=np.int16)
        for ch in range(channels):
            pcm[ch::channels] = mono
        return pcm
    return mono


def generate_sweep(duration, sample_rate, channels, freq_start=200, freq_end=8000, amplitude=0.2):
    num_samples = int(duration * sample_rate)
    t = np.arange(num_samples, dtype=np.float64) / sample_rate
    phase = 2 * np.pi * (freq_start * t + (freq_end - freq_start) * t * t / (2 * duration))
    mono = (amplitude * 32767 * np.sin(phase)).astype(np.int16)
    if channels > 1:
        pcm = np.zeros(num_samples * channels, dtype=np.int16)
        for ch in range(channels):
            pcm[ch::channels] = mono
        return pcm
    return mono


def generate_noise(duration, sample_rate, channels, amplitude=0.2):
    num_samples = int(duration * sample_rate * channels)
    noise = (amplitude * 32767 * np.random.uniform(-1.0, 1.0, num_samples)).astype(np.int16)
    return noise


# ============================================================================
# Playback logic
# ============================================================================
def choose_chunk_ms(sample_rate, channels):
    bytes_per_second = sample_rate * channels * 2
    if bytes_per_second >= 128 * 1024:
        return 200
    if bytes_per_second >= 64 * 1024:
        return 128
    return 100


class AudioPlaybackTest:
    def __init__(self, pcm_data, sample_rate, channels, chunk_ms=0, buffer_ms=1000, gesture=False, enable_head=1):
        self.pcm_data = pcm_data
        self.sample_rate = sample_rate
        self.channels = channels
        self.gesture = gesture
        self.enable_head = 1 if enable_head else 0
        self.request_title = (
            "request_audio_play_with_gesture" if gesture else "request_audio_play_data"
        )
        self.total_samples = len(pcm_data)
        self.duration = self.total_samples / (sample_rate * channels)
        self.chunk_ms = chunk_ms if chunk_ms > 0 else choose_chunk_ms(sample_rate, channels)
        self.buffer_seconds = max(buffer_ms, self.chunk_ms) / 1000.0
        frames_per_chunk = max(1, int(sample_rate * self.chunk_ms / 1000))
        self.chunk_samples = frames_per_chunk * channels

    def run(self):
        print("[%s] Config:" % TAG)
        print("  Duration:    %.1fs" % self.duration)
        print("  Sample rate: %d Hz" % self.sample_rate)
        print("  Channels:    %d" % self.channels)
        print("  Total:       %d samples" % self.total_samples)
        print("  Chunk:       %d samples (%.0fms)"
              % (self.chunk_samples,
                 self.chunk_samples * 1000.0 / (self.sample_rate * self.channels)))
        print("  Buffer:      %.0fms" % (self.buffer_seconds * 1000))
        print("  API:         %s" % self.request_title)
        print()

        print("[%s] Enabling playback control ..." % TAG)
        resp = send_request("request_audio_playback_control", {"enable": 1})
        print("[%s] playback_control: %s" % (TAG, resp.get("result", "?")))
        print()

        print("[%s] Playing ..." % TAG)
        offset = 0
        bar_width = 30
        start_time = time.monotonic()
        sent_audio = 0.0
        send_times = []

        try:
            while offset < self.total_samples:
                played_audio = time.monotonic() - start_time
                buffered_audio = sent_audio - played_audio
                if buffered_audio >= self.buffer_seconds:
                    time.sleep(min(buffered_audio - self.buffer_seconds, 0.02))
                    continue

                end = min(offset + self.chunk_samples, self.total_samples)
                chunk = self.pcm_data[offset:end]
                chunk_duration = (end - offset) / (self.sample_rate * self.channels)

                samples_list = chunk.tolist()
                send_start = time.monotonic()
                payload = {
                    "sample_rate": self.sample_rate,
                    "channels": self.channels,
                    "samples": samples_list,
                }
                if self.gesture:
                    payload["enable_head"] = self.enable_head
                send_request_no_response(self.request_title, payload)
                send_times.append(time.monotonic() - send_start)
                if len(send_times) > 50:
                    send_times.pop(0)

                elapsed = end / (self.sample_rate * self.channels)
                filled = min(int(bar_width * end / self.total_samples), bar_width)
                bar = "#" * filled + "-" * (bar_width - filled)
                avg_send_ms = sum(send_times) * 1000.0 / len(send_times)
                played_audio = time.monotonic() - start_time
                buffered_audio = sent_audio + chunk_duration - played_audio
                sys.stdout.write("\r  [%s] %.1f/%.1fs  buffer=%.0fms send=%.1fms  "
                                 % (bar, elapsed, self.duration,
                                    max(0.0, buffered_audio) * 1000.0,
                                    avg_send_ms))
                sys.stdout.flush()

                offset = end
                sent_audio += chunk_duration

        except KeyboardInterrupt:
            print("\n[%s] Interrupted by user." % TAG)

        # Send a short silent tail so the playback queue ends on zero samples;
        # stopping immediately after non-zero audio can cut the last frame and pop.
        if offset >= self.total_samples:
            tail_samples = max(
                self.channels,
                int(self.sample_rate * self.channels * TAIL_SILENCE_MS / 1000),
            )
            tail_pcm = np.zeros(tail_samples, dtype=np.int16)
            tail_offset = 0
            while tail_offset < tail_samples:
                end = min(tail_offset + self.chunk_samples, tail_samples)
                chunk = tail_pcm[tail_offset:end]

                payload = {
                    "sample_rate": self.sample_rate,
                    "channels": self.channels,
                    "samples": chunk.tolist(),
                }
                if self.gesture:
                    payload["enable_head"] = self.enable_head
                send_request_no_response(self.request_title, payload)

                sent_audio += (end - tail_offset) / (self.sample_rate * self.channels)
                tail_offset = end

        sys.stdout.write("\r  [%s] %.1f/%.1fs  \n"
                         % ("#" * bar_width, self.duration, self.duration))
        sys.stdout.flush()

        print("[%s] Waiting for playback to finish ..." % TAG)
        remaining = sent_audio - (time.monotonic() - start_time)
        time.sleep(max(0.5, remaining + 0.2))

        send_request("request_audio_playback_control", {"enable": 0})
        print("[%s] Done." % TAG)


def main():
    global ws_client

    parser = argparse.ArgumentParser(description="Audio Playback Test Tool (WebSocket)")
    parser.add_argument("file", nargs="?", default=None,
                        help="WAV file to play")
    parser.add_argument("--tone", type=int, default=0, metavar="FREQ",
                        help="Generate sine wave at FREQ Hz (e.g. --tone 1000)")
    parser.add_argument("--sweep", action="store_true",
                        help="Generate sweep signal 200~8000Hz")
    parser.add_argument("--noise", action="store_true",
                        help="Generate white noise")
    parser.add_argument("-d", "--duration", type=float, default=0,
                        help="Duration in seconds (default: 3 for generated signals)")
    parser.add_argument("-r", "--rate", type=int, default=16000,
                        help="Sample rate in Hz (default: 16000)")
    parser.add_argument("-c", "--channels", type=int, default=1,
                        help="Number of channels (default: 1)")
    parser.add_argument("-v", "--volume", type=int, default=100,
                        help="Playback volume 0~100 (default: 100)")
    parser.add_argument("-a", "--amplitude", type=float, default=0.2,
                        help="Signal amplitude 0.0~1.0 (default: 0.2, safe for 4ohm/2W speaker)")
    parser.add_argument("--gesture", action="store_true",
                        help="Use request_audio_play_with_gesture instead of request_audio_play_data")
    parser.add_argument("--enable-head", type=int, choices=(0, 1), default=1,
                        help="When using --gesture, 1 generates head motion and 0 fixes the head (default: 1)")
    parser.add_argument("--gesture-enter", action="store_true",
                        help="Enter gesture mode through request_audio_gesture_control and exit")
    parser.add_argument("--gesture-exit", action="store_true",
                        help="Exit gesture mode through request_audio_gesture_control and exit")
    parser.add_argument("--chunk-ms", type=int, default=0,
                        help="Audio chunk size in ms (default: auto)")
    parser.add_argument("--buffer-ms", type=int, default=1000,
                        help="Target playback buffer in ms (default: 1000)")
    parser.add_argument("--stop", action="store_true",
                        help="Stop current playback and exit")
    parser.add_argument("--start", action="store_true",
                        help="Start playback queue and exit")
    parser.add_argument("--host", default="10.192.1.2",
                        help="Robot IP address (default: 10.192.1.2)")
    parser.add_argument("--port", type=int, default=5000,
                        help="WebSocket port (default: 5000)")
    args = parser.parse_args()

    if args.start and args.stop:
        parser.error("Cannot combine --start and --stop")
    if args.gesture_enter and args.gesture_exit:
        parser.error("Cannot combine --gesture-enter and --gesture-exit")

    if args.start or args.stop or args.gesture_enter or args.gesture_exit:
        pass  # control mode, no playback source needed
    else:
        modes = sum([bool(args.file), bool(args.tone), args.sweep, args.noise])
        if modes == 0:
            parser.error("Specify a WAV file, --tone FREQ, --sweep, --noise, --start, or --stop")
        if modes > 1:
            parser.error("Cannot combine multiple playback modes")

    print("[%s] ==========================================" % TAG)
    print("[%s]  Audio Playback%s (WebSocket)" % (TAG, " With Gesture" if args.gesture else ""))
    print("[%s] ==========================================" % TAG)

    ready = threading.Event()

    def _on_open(ws):
        on_ws_open(ws)
        ready.set()

    ws_client = websocket.WebSocketApp(
        "ws://%s:%d" % (args.host, args.port),
        on_open=_on_open,
        on_message=on_ws_message,
        on_close=on_ws_close,
    )

    # Increase socket buffer sizes to 8MB for large message handling
    ws_client.sock_opt = [("socket", "SO_SNDBUF", 8 * 1024 * 1024)]
    ws_client.sock_opt.append(("socket", "SO_RCVBUF", 8 * 1024 * 1024))

    ws_thread = threading.Thread(target=ws_client.run_forever, daemon=True)
    ws_thread.start()

    print("[%s] Connecting to %s:%d ..." % (TAG, args.host, args.port))
    if not ready.wait(timeout=10):
        print("[%s] Connection timeout!" % TAG)
        return

    print("[%s] Waiting for ACCID ..." % TAG)
    if not _accid_event.wait(timeout=10):
        print("[%s] ACCID not received, timeout!" % TAG)
        return
    print("[%s] ACCID: %s" % (TAG, ACCID))

    # Handle --start / --stop
    if args.start:
        print("[%s] Starting playback ..." % TAG)
        send_request("request_audio_playback_control", {"enable": 1})
        print("[%s] Playback started." % TAG)
        ws_client.close()
        return

    if args.stop:
        print("[%s] Stopping playback ..." % TAG)
        send_request("request_audio_playback_control", {"enable": 0})
        print("[%s] Playback stopped." % TAG)
        ws_client.close()
        return

    if args.gesture_enter:
        print("[%s] Entering gesture mode ..." % TAG)
        resp = send_request("request_audio_gesture_control", {"enable": 1})
        print("[%s] gesture_control: %s" % (TAG, resp.get("result", "?")))
        if resp.get("message"):
            print("[%s] %s" % (TAG, resp.get("message")))
        ws_client.close()
        return

    if args.gesture_exit:
        print("[%s] Exiting gesture mode ..." % TAG)
        resp = send_request("request_audio_gesture_control", {"enable": 0})
        print("[%s] gesture_control: %s" % (TAG, resp.get("result", "?")))
        if resp.get("message"):
            print("[%s] %s" % (TAG, resp.get("message")))
        ws_client.close()
        return

    # Set volume
    if args.volume <= 100:
        print("[%s] Setting volume to %d ..." % (TAG, args.volume))
        resp = send_request("request_audio_set_volume", {"volume": args.volume})
        print("[%s] set_volume: %s" % (TAG, resp.get("result", "?")))

    try:
        if args.tone:
            duration = args.duration if args.duration > 0 else 3.0
            print("[%s] Generating %d Hz tone (%.1fs, %d Hz, %dch) ..."
                  % (TAG, args.tone, duration, args.rate, args.channels))
            pcm_data = generate_tone(args.tone, duration, args.rate, args.channels, args.amplitude)
            test = AudioPlaybackTest(pcm_data, args.rate, args.channels,
                                     args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()

        elif args.sweep:
            duration = args.duration if args.duration > 0 else 3.0
            print("[%s] Generating sweep 200~8000 Hz (%.1fs, %d Hz, %dch) ..."
                  % (TAG, duration, args.rate, args.channels))
            pcm_data = generate_sweep(duration, args.rate, args.channels, amplitude=args.amplitude)
            test = AudioPlaybackTest(pcm_data, args.rate, args.channels,
                                     args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()

        elif args.noise:
            duration = args.duration if args.duration > 0 else 3.0
            print("[%s] Generating white noise (%.1fs, %d Hz, %dch) ..."
                  % (TAG, duration, args.rate, args.channels))
            pcm_data = generate_noise(duration, args.rate, args.channels, amplitude=args.amplitude)
            test = AudioPlaybackTest(pcm_data, args.rate, args.channels,
                                     args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()

        else:
            print("[%s] Loading %s ..." % (TAG, args.file))
            pcm_data, sample_rate, channels = read_wav(args.file)
            print("[%s] Loaded: %d samples, %d Hz, %d ch"
                  % (TAG, len(pcm_data), sample_rate, channels))
            test = AudioPlaybackTest(pcm_data, sample_rate, channels,
                             args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()
    finally:
        ws_client.close()


if __name__ == "__main__":
    main()
```

### 3.6.6 播放 PCM 数据并生成手势

#### 3.6.6.1 Gesture 模式控制

控制机器人进入或退出 gesture 模式。只有先调用 `request_audio_gesture_control` 且 `enable=1` 成功后，后续 `request_audio_play_with_gesture` 才会在播放 PCM 的同时驱动上肢动作。调用 `enable=0` 用于退出 gesture 模式。未进入 gesture 模式时，`request_audio_play_with_gesture` 只播放音频，不生成动作。

##### 3.6.6.1.1 请求：request_audio_gesture_control

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_gesture_control",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "enable": 1  # 1: 进入 gesture 模式；0: 退出 gesture 模式
  }
}
```

##### 3.6.6.1.2 响应：response_audio_gesture_control

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_gesture_control",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success",  # success: 成功
                            # fail_no_enable: 缺少 enable
                            # fail_gesture_control_service_not_ready: gesture 服务未就绪
                            # fail_gesture_control_call: 调用失败
                            # fail: gesture 服务拒绝执行
      "message": "gesture mode entered"  # enable=1: gesture mode entered
                                          # enable=0: gesture mode exited
  }
}
```

##### 3.6.6.1.3 消息推送：无

#### 3.6.6.2 发送 PCM 数据并生成手势

向机器人发送 PCM 原始数据片段。系统使用同一份音频数据进行声音播放，并同步驱动机器人生成对应手势。支持分块连续发送，系统按顺序依次处理。

注意：调用前需确保音频播放服务和手势服务已启动。

![图片](data:image/jpeg;base64,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)

##### 3.6.6.2.1 请求：request_audio_play_with_gesture

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_play_with_gesture",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "sample_rate": 16000,  # 采样率，单位 Hz
      "channels": 1,         # 声道数
      "samples": [...],      # PCM 数据，int16 数组
      "enable_head": 1       # 可选；1/缺省: 生成头部动作，0: 不生成头部动作
  }
}
```

##### 3.6.6.2.2 响应：response_audio_play_with_gesture

正常成功时不返回响应；仅失败时返回响应，客户端不应等待成功响应。

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_play_with_gesture",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "fail_no_samples"  # fail_no_samples: 缺少 PCM 数据
  }
}
```

##### 3.6.6.2.3 消息推送：无

##### 3.6.6.2.4 代码示例：audio_playback_ws.py

audio_playback_ws.py --gesture-enter         # 进入手势模式

audio_playback_ws.py test.wav --gesture      # 已进入模式时，带手势播放

audio_playback_ws.py --gesture-exit          # 退出手势模式

```python
#!/usr/bin/env python3
"""
audio_playback_ws.py - Audio playback test tool (WebSocket)

Reads a WAV file or generates test tones, sends PCM data via
request_audio_play_data for playback, or request_audio_play_with_gesture
when --gesture is enabled. Gesture motion requires entering gesture mode with
request_audio_gesture_control first. Automatically calls
request_audio_playback_control to start/stop the playback queue.

Usage:
    audio_playback_ws.py test.wav                # Play WAV file
    audio_playback_ws.py --tone 1000 -d 3        # Play 1000Hz sine wave 3s
    audio_playback_ws.py --sweep -d 5            # Play 200~8000Hz sweep 5s
    audio_playback_ws.py --noise -d 3            # Play white noise 3s
    audio_playback_ws.py --host 10.192.1.2 --tone 440
    audio_playback_ws.py --tone 1000 -v 50       # Play at 50% volume
    audio_playback_ws.py --gesture-enter         # Enter gesture mode
    audio_playback_ws.py test.wav --gesture      # Play WAV file with gesture if mode entered
    audio_playback_ws.py --gesture-exit          # Exit gesture mode
    audio_playback_ws.py --start                  # Start playback queue
    audio_playback_ws.py --stop                   # Stop current playback
    audio_playback_ws.py --tone 1000 -a 0.1      # Play at 10% amplitude (speaker protection)

Dependencies:
    pip install websocket-client numpy
"""

import sys
import json
import uuid
import struct
import time
import argparse
import threading
import numpy as np
import websocket

ACCID = None
TAG = "AudioPlayback"
TAIL_SILENCE_MS = 1000

_pending = {}
_pending_lock = threading.Lock()

ws_client = None
_accid_event = threading.Event()


def generate_guid():
    return str(uuid.uuid4())


def send_request(title, data=None, timeout=10):
    global ACCID
    guid = generate_guid()
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": guid,
        "data": data or {},
    }
    evt = threading.Event()
    holder = {"resp": None}
    with _pending_lock:
        _pending[guid] = (evt, holder)

    ws_client.send(json.dumps(msg, separators=(",", ":")))

    if not evt.wait(timeout):
        with _pending_lock:
            _pending.pop(guid, None)
        raise TimeoutError("Request %s timed out after %ds" % (title, timeout))

    with _pending_lock:
        _pending.pop(guid, None)
    return holder["resp"] or {}


def send_request_no_response(title, data=None):
    global ACCID
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": generate_guid(),
        "data": data or {},
    }
    ws_client.send(json.dumps(msg, separators=(",", ":")))


def on_ws_message(ws, message):
    global ACCID
    root = json.loads(message)
    title = root.get("title", "")
    if root.get("accid"):
        ACCID = root.get("accid")
        _accid_event.set()

    if title.startswith("response_"):
        guid = root.get("guid", "")
        with _pending_lock:
            entry = _pending.get(guid)
        if entry:
            evt, holder = entry
            holder["resp"] = root.get("data", {})
            evt.set()


def on_ws_open(ws):
    print("[%s] WebSocket connected." % TAG)


def on_ws_close(ws, code, msg):
    print("[%s] WebSocket closed." % TAG)


# ============================================================================
# WAV file reader
# ============================================================================
def read_wav(filepath):
    PCM_GUID = b'\x01\x00\x00\x00\x00\x00\x10\x00\x80\x00\x00\xaa\x00\x38\x9b\x71'

    with open(filepath, "rb") as f:
        riff = f.read(4)
        if riff != b"RIFF":
            raise ValueError("Not a RIFF file")
        f.read(4)
        wave = f.read(4)
        if wave != b"WAVE":
            raise ValueError("Not a WAVE file")

        sample_rate = 0
        channels = 0
        bits_per_sample = 0
        pcm_data = None

        while True:
            chunk_header = f.read(8)
            if len(chunk_header) < 8:
                break
            chunk_id = chunk_header[:4]
            chunk_size = struct.unpack("<I", chunk_header[4:8])[0]

            if chunk_id == b"fmt ":
                fmt_data = f.read(chunk_size)
                audio_format = struct.unpack("<H", fmt_data[0:2])[0]
                channels = struct.unpack("<H", fmt_data[2:4])[0]
                sample_rate = struct.unpack("<I", fmt_data[4:8])[0]
                bits_per_sample = struct.unpack("<H", fmt_data[14:16])[0]

                if audio_format == 65534 and len(fmt_data) >= 40:
                    valid_bits = struct.unpack("<H", fmt_data[18:20])[0]
                    sub_format = fmt_data[24:40]
                    if sub_format == PCM_GUID:
                        audio_format = 1
                    if valid_bits > 0:
                        bits_per_sample = valid_bits

                if audio_format != 1:
                    raise ValueError("Unsupported audio format: %d" % audio_format)

            elif chunk_id == b"data":
                raw = f.read(chunk_size)
                if bits_per_sample == 16:
                    pcm_data = np.frombuffer(raw, dtype=np.int16)
                elif bits_per_sample == 8:
                    pcm_data = (np.frombuffer(raw, dtype=np.uint8).astype(np.int16) - 128) * 256
                elif bits_per_sample == 24:
                    num_samples = len(raw) // 3
                    pcm_data = np.zeros(num_samples, dtype=np.int16)
                    for i in range(num_samples):
                        b0, b1, b2 = raw[i*3], raw[i*3+1], raw[i*3+2]
                        sample32 = (b2 << 24) | (b1 << 16) | (b0 << 8)
                        if sample32 >= 0x80000000:
                            sample32 -= 0x100000000
                        pcm_data[i] = np.int16(sample32 >> 16)
                elif bits_per_sample == 32:
                    raw32 = np.frombuffer(raw, dtype=np.int32)
                    pcm_data = (raw32 >> 16).astype(np.int16)
                else:
                    raise ValueError("Unsupported bits_per_sample: %d" % bits_per_sample)
                break
            else:
                skip = chunk_size
                if skip & 1:
                    skip += 1
                f.seek(skip, 1)

    if pcm_data is None:
        raise ValueError("No data chunk found in WAV file")
    return pcm_data, sample_rate, channels


# ============================================================================
# Test tone generators
# ============================================================================
def generate_tone(freq, duration, sample_rate, channels, amplitude=0.2):
    num_samples = int(duration * sample_rate)
    t = np.arange(num_samples, dtype=np.float64) / sample_rate
    mono = (amplitude * 32767 * np.sin(2 * np.pi * freq * t)).astype(np.int16)
    if channels > 1:
        pcm = np.zeros(num_samples * channels, dtype=np.int16)
        for ch in range(channels):
            pcm[ch::channels] = mono
        return pcm
    return mono


def generate_sweep(duration, sample_rate, channels, freq_start=200, freq_end=8000, amplitude=0.2):
    num_samples = int(duration * sample_rate)
    t = np.arange(num_samples, dtype=np.float64) / sample_rate
    phase = 2 * np.pi * (freq_start * t + (freq_end - freq_start) * t * t / (2 * duration))
    mono = (amplitude * 32767 * np.sin(phase)).astype(np.int16)
    if channels > 1:
        pcm = np.zeros(num_samples * channels, dtype=np.int16)
        for ch in range(channels):
            pcm[ch::channels] = mono
        return pcm
    return mono


def generate_noise(duration, sample_rate, channels, amplitude=0.2):
    num_samples = int(duration * sample_rate * channels)
    noise = (amplitude * 32767 * np.random.uniform(-1.0, 1.0, num_samples)).astype(np.int16)
    return noise


# ============================================================================
# Playback logic
# ============================================================================
def choose_chunk_ms(sample_rate, channels):
    bytes_per_second = sample_rate * channels * 2
    if bytes_per_second >= 128 * 1024:
        return 200
    if bytes_per_second >= 64 * 1024:
        return 128
    return 100


class AudioPlaybackTest:
    def __init__(self, pcm_data, sample_rate, channels, chunk_ms=0, buffer_ms=1000, gesture=False, enable_head=1):
        self.pcm_data = pcm_data
        self.sample_rate = sample_rate
        self.channels = channels
        self.gesture = gesture
        self.enable_head = 1 if enable_head else 0
        self.request_title = (
            "request_audio_play_with_gesture" if gesture else "request_audio_play_data"
        )
        self.total_samples = len(pcm_data)
        self.duration = self.total_samples / (sample_rate * channels)
        self.chunk_ms = chunk_ms if chunk_ms > 0 else choose_chunk_ms(sample_rate, channels)
        self.buffer_seconds = max(buffer_ms, self.chunk_ms) / 1000.0
        frames_per_chunk = max(1, int(sample_rate * self.chunk_ms / 1000))
        self.chunk_samples = frames_per_chunk * channels

    def run(self):
        print("[%s] Config:" % TAG)
        print("  Duration:    %.1fs" % self.duration)
        print("  Sample rate: %d Hz" % self.sample_rate)
        print("  Channels:    %d" % self.channels)
        print("  Total:       %d samples" % self.total_samples)
        print("  Chunk:       %d samples (%.0fms)"
              % (self.chunk_samples,
                 self.chunk_samples * 1000.0 / (self.sample_rate * self.channels)))
        print("  Buffer:      %.0fms" % (self.buffer_seconds * 1000))
        print("  API:         %s" % self.request_title)
        print()

        print("[%s] Enabling playback control ..." % TAG)
        resp = send_request("request_audio_playback_control", {"enable": 1})
        print("[%s] playback_control: %s" % (TAG, resp.get("result", "?")))
        print()

        print("[%s] Playing ..." % TAG)
        offset = 0
        bar_width = 30
        start_time = time.monotonic()
        sent_audio = 0.0
        send_times = []

        try:
            while offset < self.total_samples:
                played_audio = time.monotonic() - start_time
                buffered_audio = sent_audio - played_audio
                if buffered_audio >= self.buffer_seconds:
                    time.sleep(min(buffered_audio - self.buffer_seconds, 0.02))
                    continue

                end = min(offset + self.chunk_samples, self.total_samples)
                chunk = self.pcm_data[offset:end]
                chunk_duration = (end - offset) / (self.sample_rate * self.channels)

                samples_list = chunk.tolist()
                send_start = time.monotonic()
                payload = {
                    "sample_rate": self.sample_rate,
                    "channels": self.channels,
                    "samples": samples_list,
                }
                if self.gesture:
                    payload["enable_head"] = self.enable_head
                send_request_no_response(self.request_title, payload)
                send_times.append(time.monotonic() - send_start)
                if len(send_times) > 50:
                    send_times.pop(0)

                elapsed = end / (self.sample_rate * self.channels)
                filled = min(int(bar_width * end / self.total_samples), bar_width)
                bar = "#" * filled + "-" * (bar_width - filled)
                avg_send_ms = sum(send_times) * 1000.0 / len(send_times)
                played_audio = time.monotonic() - start_time
                buffered_audio = sent_audio + chunk_duration - played_audio
                sys.stdout.write("\r  [%s] %.1f/%.1fs  buffer=%.0fms send=%.1fms  "
                                 % (bar, elapsed, self.duration,
                                    max(0.0, buffered_audio) * 1000.0,
                                    avg_send_ms))
                sys.stdout.flush()

                offset = end
                sent_audio += chunk_duration

        except KeyboardInterrupt:
            print("\n[%s] Interrupted by user." % TAG)

        # Send a short silent tail so the playback queue ends on zero samples;
        # stopping immediately after non-zero audio can cut the last frame and pop.
        if offset >= self.total_samples:
            tail_samples = max(
                self.channels,
                int(self.sample_rate * self.channels * TAIL_SILENCE_MS / 1000),
            )
            tail_pcm = np.zeros(tail_samples, dtype=np.int16)
            tail_offset = 0
            while tail_offset < tail_samples:
                end = min(tail_offset + self.chunk_samples, tail_samples)
                chunk = tail_pcm[tail_offset:end]

                payload = {
                    "sample_rate": self.sample_rate,
                    "channels": self.channels,
                    "samples": chunk.tolist(),
                }
                if self.gesture:
                    payload["enable_head"] = self.enable_head
                send_request_no_response(self.request_title, payload)

                sent_audio += (end - tail_offset) / (self.sample_rate * self.channels)
                tail_offset = end

        sys.stdout.write("\r  [%s] %.1f/%.1fs  \n"
                         % ("#" * bar_width, self.duration, self.duration))
        sys.stdout.flush()

        print("[%s] Waiting for playback to finish ..." % TAG)
        remaining = sent_audio - (time.monotonic() - start_time)
        time.sleep(max(0.5, remaining + 0.2))

        send_request("request_audio_playback_control", {"enable": 0})
        print("[%s] Done." % TAG)


def main():
    global ws_client

    parser = argparse.ArgumentParser(description="Audio Playback Test Tool (WebSocket)")
    parser.add_argument("file", nargs="?", default=None,
                        help="WAV file to play")
    parser.add_argument("--tone", type=int, default=0, metavar="FREQ",
                        help="Generate sine wave at FREQ Hz (e.g. --tone 1000)")
    parser.add_argument("--sweep", action="store_true",
                        help="Generate sweep signal 200~8000Hz")
    parser.add_argument("--noise", action="store_true",
                        help="Generate white noise")
    parser.add_argument("-d", "--duration", type=float, default=0,
                        help="Duration in seconds (default: 3 for generated signals)")
    parser.add_argument("-r", "--rate", type=int, default=16000,
                        help="Sample rate in Hz (default: 16000)")
    parser.add_argument("-c", "--channels", type=int, default=1,
                        help="Number of channels (default: 1)")
    parser.add_argument("-v", "--volume", type=int, default=100,
                        help="Playback volume 0~100 (default: 100)")
    parser.add_argument("-a", "--amplitude", type=float, default=0.2,
                        help="Signal amplitude 0.0~1.0 (default: 0.2, safe for 4ohm/2W speaker)")
    parser.add_argument("--gesture", action="store_true",
                        help="Use request_audio_play_with_gesture instead of request_audio_play_data")
    parser.add_argument("--enable-head", type=int, choices=(0, 1), default=1,
                        help="When using --gesture, 1 generates head motion and 0 fixes the head (default: 1)")
    parser.add_argument("--gesture-enter", action="store_true",
                        help="Enter gesture mode through request_audio_gesture_control and exit")
    parser.add_argument("--gesture-exit", action="store_true",
                        help="Exit gesture mode through request_audio_gesture_control and exit")
    parser.add_argument("--chunk-ms", type=int, default=0,
                        help="Audio chunk size in ms (default: auto)")
    parser.add_argument("--buffer-ms", type=int, default=1000,
                        help="Target playback buffer in ms (default: 1000)")
    parser.add_argument("--stop", action="store_true",
                        help="Stop current playback and exit")
    parser.add_argument("--start", action="store_true",
                        help="Start playback queue and exit")
    parser.add_argument("--host", default="10.192.1.2",
                        help="Robot IP address (default: 10.192.1.2)")
    parser.add_argument("--port", type=int, default=5000,
                        help="WebSocket port (default: 5000)")
    args = parser.parse_args()

    if args.start and args.stop:
        parser.error("Cannot combine --start and --stop")
    if args.gesture_enter and args.gesture_exit:
        parser.error("Cannot combine --gesture-enter and --gesture-exit")

    if args.start or args.stop or args.gesture_enter or args.gesture_exit:
        pass  # control mode, no playback source needed
    else:
        modes = sum([bool(args.file), bool(args.tone), args.sweep, args.noise])
        if modes == 0:
            parser.error("Specify a WAV file, --tone FREQ, --sweep, --noise, --start, or --stop")
        if modes > 1:
            parser.error("Cannot combine multiple playback modes")

    print("[%s] ==========================================" % TAG)
    print("[%s]  Audio Playback%s (WebSocket)" % (TAG, " With Gesture" if args.gesture else ""))
    print("[%s] ==========================================" % TAG)

    ready = threading.Event()

    def _on_open(ws):
        on_ws_open(ws)
        ready.set()

    ws_client = websocket.WebSocketApp(
        "ws://%s:%d" % (args.host, args.port),
        on_open=_on_open,
        on_message=on_ws_message,
        on_close=on_ws_close,
    )

    # Increase socket buffer sizes to 8MB for large message handling
    ws_client.sock_opt = [("socket", "SO_SNDBUF", 8 * 1024 * 1024)]
    ws_client.sock_opt.append(("socket", "SO_RCVBUF", 8 * 1024 * 1024))

    ws_thread = threading.Thread(target=ws_client.run_forever, daemon=True)
    ws_thread.start()

    print("[%s] Connecting to %s:%d ..." % (TAG, args.host, args.port))
    if not ready.wait(timeout=10):
        print("[%s] Connection timeout!" % TAG)
        return

    print("[%s] Waiting for ACCID ..." % TAG)
    if not _accid_event.wait(timeout=10):
        print("[%s] ACCID not received, timeout!" % TAG)
        return
    print("[%s] ACCID: %s" % (TAG, ACCID))

    # Handle --start / --stop
    if args.start:
        print("[%s] Starting playback ..." % TAG)
        send_request("request_audio_playback_control", {"enable": 1})
        print("[%s] Playback started." % TAG)
        ws_client.close()
        return

    if args.stop:
        print("[%s] Stopping playback ..." % TAG)
        send_request("request_audio_playback_control", {"enable": 0})
        print("[%s] Playback stopped." % TAG)
        ws_client.close()
        return

    if args.gesture_enter:
        print("[%s] Entering gesture mode ..." % TAG)
        resp = send_request("request_audio_gesture_control", {"enable": 1})
        print("[%s] gesture_control: %s" % (TAG, resp.get("result", "?")))
        if resp.get("message"):
            print("[%s] %s" % (TAG, resp.get("message")))
        ws_client.close()
        return

    if args.gesture_exit:
        print("[%s] Exiting gesture mode ..." % TAG)
        resp = send_request("request_audio_gesture_control", {"enable": 0})
        print("[%s] gesture_control: %s" % (TAG, resp.get("result", "?")))
        if resp.get("message"):
            print("[%s] %s" % (TAG, resp.get("message")))
        ws_client.close()
        return

    # Set volume
    if args.volume <= 100:
        print("[%s] Setting volume to %d ..." % (TAG, args.volume))
        resp = send_request("request_audio_set_volume", {"volume": args.volume})
        print("[%s] set_volume: %s" % (TAG, resp.get("result", "?")))

    try:
        if args.tone:
            duration = args.duration if args.duration > 0 else 3.0
            print("[%s] Generating %d Hz tone (%.1fs, %d Hz, %dch) ..."
                  % (TAG, args.tone, duration, args.rate, args.channels))
            pcm_data = generate_tone(args.tone, duration, args.rate, args.channels, args.amplitude)
            test = AudioPlaybackTest(pcm_data, args.rate, args.channels,
                                     args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()

        elif args.sweep:
            duration = args.duration if args.duration > 0 else 3.0
            print("[%s] Generating sweep 200~8000 Hz (%.1fs, %d Hz, %dch) ..."
                  % (TAG, duration, args.rate, args.channels))
            pcm_data = generate_sweep(duration, args.rate, args.channels, amplitude=args.amplitude)
            test = AudioPlaybackTest(pcm_data, args.rate, args.channels,
                                     args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()

        elif args.noise:
            duration = args.duration if args.duration > 0 else 3.0
            print("[%s] Generating white noise (%.1fs, %d Hz, %dch) ..."
                  % (TAG, duration, args.rate, args.channels))
            pcm_data = generate_noise(duration, args.rate, args.channels, amplitude=args.amplitude)
            test = AudioPlaybackTest(pcm_data, args.rate, args.channels,
                                     args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()

        else:
            print("[%s] Loading %s ..." % (TAG, args.file))
            pcm_data, sample_rate, channels = read_wav(args.file)
            print("[%s] Loaded: %d samples, %d Hz, %d ch"
                  % (TAG, len(pcm_data), sample_rate, channels))
            test = AudioPlaybackTest(pcm_data, sample_rate, channels,
                             args.chunk_ms, args.buffer_ms, args.gesture, args.enable_head)
            test.run()
    finally:
        ws_client.close()


if __name__ == "__main__":
    main()
```

### 3.6.7 播放音频文件

请求播放音频文件。支持机器人本地文件路径或远程 HTTP URL，支持 WAV、MP3、PCM 格式。

#### 3.6.7.1 请求：request_audio_play_file

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_play_file",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "file_path": "/path/to/audio.wav"  # 本地文件路径或 HTTP URL
  }
}
```

#### 3.6.7.2 响应：response_audio_play_file

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_play_file",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功
  }
}
```

#### 3.6.7.3 消息推送：无

#### 3.6.7.4 代码示例：audio_file_player_ws.py

audio_file_player_ws.py /path/to/audio.wav

audio_file_player_ws.py https://example.com/audio.wav

```python
#!/usr/bin/env python3
"""
audio_file_player_ws.py - File playback test tool (WebSocket)

Requests the backend to play a WAV file (local path or URL)
via request_audio_play_file.

Usage:
    audio_file_player_ws.py /path/to/audio.wav
    audio_file_player_ws.py https://download.samplelib.com/wav/sample-3s.wav
    audio_file_player_ws.py --host 10.192.1.2 /path/to/audio.wav
    audio_file_player_ws.py -v 30 /path/to/audio.wav   # Play at 30% volume

Dependencies:
    pip install websocket-client
"""

import json
import uuid
import time
import argparse
import threading
import websocket

ACCID = None
TAG = "AudioFilePlayer"

_pending = {}
_pending_lock = threading.Lock()

ws_client = None
_accid_event = threading.Event()


def generate_guid():
    return str(uuid.uuid4())


def send_request(title, data=None, timeout=10):
    global ACCID
    guid = generate_guid()
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": guid,
        "data": data or {},
    }
    evt = threading.Event()
    holder = {"resp": None}
    with _pending_lock:
        _pending[guid] = (evt, holder)

    ws_client.send(json.dumps(msg))

    if not evt.wait(timeout):
        with _pending_lock:
            _pending.pop(guid, None)
        raise TimeoutError("Request %s timed out after %ds" % (title, timeout))

    with _pending_lock:
        _pending.pop(guid, None)
    return holder["resp"] or {}


def on_ws_message(ws, message):
    global ACCID
    root = json.loads(message)
    title = root.get("title", "")
    if root.get("accid"):
        ACCID = root.get("accid")
        _accid_event.set()

    if title.startswith("response_"):
        guid = root.get("guid", "")
        with _pending_lock:
            entry = _pending.get(guid)
        if entry:
            evt, holder = entry
            holder["resp"] = root.get("data", {})
            evt.set()


def on_ws_open(ws):
    print("[%s] WebSocket connected." % TAG)


def on_ws_close(ws, code, msg):
    print("[%s] WebSocket closed." % TAG)


# ============================================================================
# Play file logic
# ============================================================================
def play_file(path_or_url):
    print("[%s] Calling request_audio_play_file ..." % TAG)
    print("[%s]   path: %s" % (TAG, path_or_url))

    resp = send_request("request_audio_play_file",
                        {"file_path": path_or_url}, timeout=180)

    result = resp.get("result", "fail")
    if result == "success":
        print("[%s] OK" % TAG)
    else:
        print("[%s] FAIL: %s" % (TAG, resp.get("message", result)))
    return result == "success"


def main():
    global ws_client

    parser = argparse.ArgumentParser(description="Audio File Player Test Tool (WebSocket)")
    parser.add_argument("file", help="WAV file path or URL to play")
    parser.add_argument("-v", "--volume", type=int, default=100,
                        help="Playback volume 0~100 (default: 100)")
    parser.add_argument("--host", default="10.192.1.2",
                        help="Robot IP address (default: 10.192.1.2)")
    parser.add_argument("--port", type=int, default=5000,
                        help="WebSocket port (default: 5000)")
    args = parser.parse_args()

    print("[%s] ==========================================" % TAG)
    print("[%s]  Audio File Player (WebSocket)" % TAG)
    print("[%s] ==========================================" % TAG)

    ready = threading.Event()

    def _on_open(ws):
        on_ws_open(ws)
        ready.set()

    ws_client = websocket.WebSocketApp(
        "ws://%s:%d" % (args.host, args.port),
        on_open=_on_open,
        on_message=on_ws_message,
        on_close=on_ws_close,
    )

    ws_thread = threading.Thread(target=ws_client.run_forever, daemon=True)
    ws_thread.start()

    print("[%s] Connecting to %s:%d ..." % (TAG, args.host, args.port))
    if not ready.wait(timeout=10):
        print("[%s] Connection timeout!" % TAG)
        return

    print("[%s] Waiting for ACCID ..." % TAG)
    if not _accid_event.wait(timeout=10):
        print("[%s] ACCID not received, timeout!" % TAG)
        return
    print("[%s] ACCID: %s" % (TAG, ACCID))

    # Set volume
    if args.volume <= 100:
        print("[%s] Setting volume to %d ..." % (TAG, args.volume))
        resp = send_request("request_audio_set_volume", {"volume": args.volume})
        print("[%s] set_volume: %s" % (TAG, resp.get("result", "?")))

    try:
        play_file(args.file)
    finally:
        ws_client.close()

    print("[%s] Done." % TAG)


if __name__ == "__main__":
    main()
```

### 3.6.8 唤醒词检测控制

唤醒词检测的启停开关。开启后，系统会持续检测音频流中的唤醒词，检测到匹配时向客户端推送 `notify_audio_wakeup` 事件。

#### 3.6.8.1 请求：request_audio_wakeup_control

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_wakeup_control",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "enable": 1  # 1: 开启唤醒检测, 0: 关闭唤醒检测
  }
}
```

#### 3.6.8.2 响应：response_audio_wakeup_control

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_wakeup_control",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功
  }
}
```

#### 3.6.8.3 消息推送：notify_audio_wakeup

当唤醒检测开启时，检测到用户唤醒词后触发此事件。

```json
{
  "accid": "HU_D04_01_001",
  "title": "notify_audio_wakeup",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "word": "hai4 o1 li3",  # 触发的唤醒词
      "doa": 180              # 声源方向角度 (DOA)，单位度
  }
}
```

### 3.6.9 设置唤醒词

动态设置唤醒词。设置成功后立即生效并持久化存储，重启后自动恢复。

此功能需要机器人配备语音唤醒模块。

#### 3.6.9.1 请求：request_audio_set_wakeup_word

| 字段 | 说明 | 是否必填 |
| ---- | ---- | -------- |
| word | 拼音加声调（谐音） | 必填 |

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_set_wakeup_word",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "word": "ni3 hao3 zhu2 ji4"  # 使用拼音加声调
  }
}
```

#### 3.6.9.2 响应：response_audio_set_wakeup_word

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_set_wakeup_word",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功
  }
}
```

#### 3.6.9.3 消息推送：无

#### 3.6.9.4 代码示例：audio_wakeup_ws.py

audio_wakeup_ws.py set "ni3 hao3 zhu2 ji4"   # 简单唤醒词，带声调拼音

audio_wakeup_ws.py get                       # 获取当前唤醒词

audio_wakeup_ws.py enable                    # 开启唤醒检测

audio_wakeup_ws.py disable                   # 关闭唤醒检测

audio_wakeup_ws.py listen                    # 监听唤醒事件（Ctrl+C 退出）

audio_wakeup_ws.py listen -d 30              # 监听 30 秒

audio_wakeup_ws.py --host 10.192.1.4 listen

```python
#!/usr/bin/env python3
"""
audio_wakeup_ws.py - Wakeup word test tool (WebSocket)

Provides wakeup feature control and testing:
  - Set wakeup word (with optional pinyin/thresh/greeting for aispeech)
  - Enable/disable wakeup detection
  - Listen for wakeup events

Usage:
    # Oli (simple word, pinyin with tones):
    audio_wakeup_ws.py set "ni3 hao3 zhu2 ji4"

    # Oli Lite (full format with pinyin, threshold, greeting):
    audio_wakeup_ws.py set "你好逐际" --pinyin "ni hao zhu ji" --thresh 0.38 --greeting "我在,有什么可以帮您"

    # Other commands:
    audio_wakeup_ws.py get                        # Get current wakeup word
    audio_wakeup_ws.py enable                     # Enable wakeup detection
    audio_wakeup_ws.py disable                    # Disable wakeup detection
    audio_wakeup_ws.py listen                     # Listen for events (Ctrl+C)
    audio_wakeup_ws.py listen -d 30               # Listen for 30 seconds
    audio_wakeup_ws.py --host 10.192.1.4 listen

Dependencies:
    pip install websocket-client
"""

import json
import uuid
import time
import argparse
import threading
import websocket

ACCID = None
TAG = "AudioWakeup"

_pending = {}
_pending_lock = threading.Lock()

_notify_cbs = {}

ws_client = None
_accid_event = threading.Event()


def generate_guid():
    return str(uuid.uuid4())


def send_request(title, data=None, timeout=10):
    global ACCID
    guid = generate_guid()
    msg = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": guid,
        "data": data or {},
    }
    evt = threading.Event()
    holder = {"resp": None}
    with _pending_lock:
        _pending[guid] = (evt, holder)

    ws_client.send(json.dumps(msg))

    if not evt.wait(timeout):
        with _pending_lock:
            _pending.pop(guid, None)
        raise TimeoutError("Request %s timed out after %ds" % (title, timeout))

    with _pending_lock:
        _pending.pop(guid, None)
    return holder["resp"] or {}


def on_ws_message(ws, message):
    global ACCID
    root = json.loads(message)
    title = root.get("title", "")
    if root.get("accid"):
        ACCID = root.get("accid")
        _accid_event.set()

    if title.startswith("response_"):
        guid = root.get("guid", "")
        with _pending_lock:
            entry = _pending.get(guid)
        if entry:
            evt, holder = entry
            holder["resp"] = root.get("data", {})
            evt.set()
    elif title.startswith("notify_"):
        cb = _notify_cbs.get(title)
        if cb:
            try:
                cb(root.get("data", {}))
            except Exception:
                pass


def on_ws_open(ws):
    print("[%s] WebSocket connected." % TAG)


def on_ws_close(ws, code, msg):
    print("[%s] WebSocket closed." % TAG)


# ============================================================================
# Wakeup commands
# ============================================================================
def set_wakeup_word(word, pinyin="", thresh="", greeting="", subsets=""):
    """Set wakeup word. For aispeech, pinyin/thresh/greeting are recommended."""
    data = {"word": word}
    if pinyin:
        data["pinyin"] = pinyin
    if thresh:
        data["thresh"] = thresh
    if greeting:
        data["greeting"] = greeting
    if subsets:
        data["subsets"] = subsets

    if pinyin:
        print("[%s] Setting wakeup word: %s (pinyin=%s)" % (TAG, word, pinyin))
    else:
        print("[%s] Setting wakeup word: %s" % (TAG, word))

    resp = send_request("request_audio_set_wakeup_word", data)
    result = resp.get("result", "fail")
    if result == "success":
        print("[%s] OK: %s" % (TAG, resp.get("message", "")))
    else:
        print("[%s] FAIL: %s" % (TAG, resp.get("message", result)))
    return result == "success"


def get_wakeup_word():
    print("[%s] Getting current wakeup word ..." % TAG)
    resp = send_request("request_audio_get_wakeup_word")
    result = resp.get("result", "fail")
    if result == "success":
        word = resp.get("word", "")
        backend = resp.get("backend", "")
        print("[%s] Word:     %s" % (TAG, word if word else "(not set)"))
        if backend:
            print("[%s] Backend:  %s" % (TAG, backend))
        if resp.get("pinyin"):
            print("[%s] Pinyin:   %s" % (TAG, resp["pinyin"]))
        if resp.get("thresh"):
            print("[%s] Thresh:   %s" % (TAG, resp["thresh"]))
        if resp.get("greeting"):
            print("[%s] Greeting: %s" % (TAG, resp["greeting"]))
        if resp.get("subsets"):
            print("[%s] Subsets:  %s" % (TAG, resp["subsets"]))
    else:
        print("[%s] FAIL: %s" % (TAG, resp.get("message", result)))


def wakeup_control(enable):
    action = "enable" if enable else "disable"
    print("[%s] %s wakeup detection ..." % (TAG, action.capitalize()))
    resp = send_request("request_audio_wakeup_control", {"enable": 1 if enable else 0})
    result = resp.get("result", "fail")
    if result == "success":
        print("[%s] OK" % TAG)
    else:
        print("[%s] FAIL: %s" % (TAG, resp.get("message", result)))
    return result == "success"


def listen_wakeup(duration):
    count = [0]

    def on_wakeup(data):
        count[0] += 1
        word = data.get("word", "?")
        doa = data.get("doa", "?")
        print("[%s] [#%d] Wakeup event: word=%s, doa=%s" % (TAG, count[0], word, doa))

    _notify_cbs["notify_audio_wakeup"] = on_wakeup

    if duration > 0:
        print("[%s] Listening for wakeup events (%ds) ..." % (TAG, duration))
        print("[%s] Press Ctrl+C to stop early." % TAG)
        try:
            time.sleep(duration)
        except KeyboardInterrupt:
            pass
    else:
        print("[%s] Listening for wakeup events (Ctrl+C to stop) ..." % TAG)
        try:
            while True:
                time.sleep(1)
        except KeyboardInterrupt:
            pass

    _notify_cbs.pop("notify_audio_wakeup", None)
    print("[%s] Stopped. Total events: %d" % (TAG, count[0]))


def main():
    global ws_client

    parser = argparse.ArgumentParser(description="Audio Wakeup Test Tool (WebSocket)")
    parser.add_argument("--host", default="10.192.1.2",
                        help="Robot IP address (default: 10.192.1.2)")
    parser.add_argument("--port", type=int, default=5000,
                        help="WebSocket port (default: 5000)")

    subparsers = parser.add_subparsers(dest="command", help="command")

    p_set = subparsers.add_parser("set", help="Set wakeup word")
    p_set.add_argument("word", help="Wakeup word to set")
    p_set.add_argument("--pinyin", default="", help="Pinyin (aispeech: required, e.g. 'ni hao zhu ji')")
    p_set.add_argument("--thresh", default="", help="Wakeup threshold (default: 0.38)")
    p_set.add_argument("--greeting", default="", help="Greeting response text")
    p_set.add_argument("--subsets", default="", help="Wakeup word subsets (e.g. '你好逐际|好逐际|逐际')")

    subparsers.add_parser("get", help="Get current wakeup word")
    subparsers.add_parser("enable", help="Enable wakeup detection")
    subparsers.add_parser("disable", help="Disable wakeup detection")

    p_listen = subparsers.add_parser("listen", help="Listen for wakeup events")
    p_listen.add_argument("-d", "--duration", type=int, default=0,
                          help="Listen duration in seconds (0=forever, default: 0)")

    args = parser.parse_args()

    if not args.command:
        parser.print_help()
        return

    print("[%s] ==========================================" % TAG)
    print("[%s]  Audio Wakeup (WebSocket)" % TAG)
    print("[%s] ==========================================" % TAG)

    ready = threading.Event()

    def _on_open(ws):
        on_ws_open(ws)
        ready.set()

    ws_client = websocket.WebSocketApp(
        "ws://%s:%d" % (args.host, args.port),
        on_open=_on_open,
        on_message=on_ws_message,
        on_close=on_ws_close,
    )

    ws_thread = threading.Thread(target=ws_client.run_forever, daemon=True)
    ws_thread.start()

    print("[%s] Connecting to %s:%d ..." % (TAG, args.host, args.port))
    if not ready.wait(timeout=10):
        print("[%s] Connection timeout!" % TAG)
        return

    print("[%s] Waiting for ACCID ..." % TAG)
    if not _accid_event.wait(timeout=10):
        print("[%s] ACCID not received, timeout!" % TAG)
        return
    print("[%s] ACCID: %s" % (TAG, ACCID))

    try:
        if args.command == "get":
            get_wakeup_word()
        elif args.command == "set":
            set_wakeup_word(args.word, args.pinyin, args.thresh, args.greeting, args.subsets)
        elif args.command == "enable":
            wakeup_control(True)
        elif args.command == "disable":
            wakeup_control(False)
        elif args.command == "listen":
            listen_wakeup(args.duration)
    finally:
        ws_client.close()

    print("[%s] Done." % TAG)


if __name__ == "__main__":
    main()
```

### 3.6.10 查询唤醒词

查询当前设定的唤醒词。

#### 3.6.10.1 请求：request_audio_get_wakeup_word

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_get_wakeup_word",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.6.10.2 响应：response_audio_get_wakeup_word

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_get_wakeup_word",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success",
      "word": "ni3 hao3 zhu2 ji4",
      "backend": "aispeech"
  }
}
```

#### 3.6.10.3 消息推送：无

### 3.6.11 设置音量

设置播放的全局音量。

#### 3.6.11.1 请求：request_audio_set_volume

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_set_volume",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "volume": 50  # 音量值，取值范围 [0, 100]，0 为静音，100 为最大音量
  }
}
```

#### 3.6.11.2 响应：response_audio_set_volume

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_set_volume",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: 成功
  }
}
```

#### 3.6.11.3 消息推送：无

### 3.6.12 查询音量

查询当前播放的全局音量。

#### 3.6.12.1 请求：request_audio_get_volume

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_get_volume",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 3.6.12.2 响应：response_audio_get_volume

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_get_volume",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success",
      "volume": 50,
      "message": "volume=50"
  }
}
```

#### 3.6.12.3 消息推送：无

### 3.6.13 远程音频注入

外部设备（如手机、Pad）将拾取的 PCM 音频数据注入到机器人系统中，机器人服务会将该数据转发给除发送者以外的其他已连接 WebSocket 客户端。

典型场景：手机端拾音后，将音频数据发送给机器人，机器人上运行的其他应用（如语音识别、对话系统）通过 WebSocket 接收并处理该音频流，从而代替本地麦克风拾音。

![图片](data:image/jpeg;base64,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)

#### 3.6.13.1 请求：request_audio_inject_pcm

```json
{
  "accid": "HU_D04_01_001",
  "title": "request_audio_inject_pcm",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "sample_rate": 16000,   # 采样率，单位 Hz
      "channels": 1,          # 声道数
      "samples": "<数据格式，由收发双方自行约定，如：PCM int16 或 base64>"
  }
}
```

#### 3.6.13.2 响应：response_audio_inject_pcm

```json
{
  "accid": "HU_D04_01_001",
  "title": "response_audio_inject_pcm",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"     # success: 成功
  }
}
```

错误码说明：

| result | 说明 |
| ------ | ---- |
| success | 成功 |
| fail_no_sample_rate | 缺少 sample_rate 字段 |
| fail_no_channels | 缺少 channels 字段 |
| fail_no_samples | 缺少 samples 字段 |

#### 3.6.13.3 消息推送：notify_audio_inject_pcm

请求成功后，会将音频数据推送给除发送者以外的所有已连接 WebSocket 客户端。

```json
{
  "accid": "HU_D04_01_001",
  "title": "notify_audio_inject_pcm",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "sample_rate": 16000,   # 采样率，单位 Hz
      "channels": 1,          # 声道数
      "samples": "<与请求中完全一致>"
  }
}
```

#### 3.6.13.4 代码示例：audio_inject_pcm_ws.py

audio_inject_pcm_ws.py --host 10.192.1.2                              # 注入 1 秒 440Hz 正弦波（int16 数组，默认）

python3 audio_inject_pcm_ws.py --host 10.192.1.2 --format base64     # 使用 base64 编码注入

audio_inject_pcm_ws.py --host 10.192.1.2 --wav /path/to/audio.wav    # 从 WAV 文件注入

audio_inject_pcm_ws.py --host 10.192.1.2 --listen -o received.wav    # 监听 notify_audio_inject_pcm 并保存为 WAV

```python
#!/usr/bin/env python3
"""
audio_inject_pcm_ws.py - Audio PCM inject test tool (WebSocket)

Tests request_audio_inject_pcm with PCM data (int16 array or base64).
The server does NOT parse the samples value — it validates field existence
and forwards root["data"] as-is to all other clients via notify_audio_inject_pcm.

Usage:
    # Inject 1s 440Hz sine wave (int16 array, default)
    python3 audio_inject_pcm_ws.py --host 10.192.1.2

    # Inject with base64 encoding
    python3 audio_inject_pcm_ws.py --host 10.192.1.2 --format base64

    # Inject from WAV file
    python3 audio_inject_pcm_ws.py --host 10.192.1.2 --wav /path/to/audio.wav

    # Listen for notify_audio_inject_pcm broadcasts and save to WAV
    python3 audio_inject_pcm_ws.py --host 10.192.1.2 --listen -o received.wav

Dependencies:
    pip install websocket-client numpy
"""

import sys
import json
import uuid
import struct
import math
import time
import base64
import signal
import argparse
import threading

try:
    import numpy as np
except ImportError:
    print("pip install numpy")
    sys.exit(1)

try:
    import websocket
except ImportError:
    print("pip install websocket-client")
    sys.exit(1)


TAG = "AudioInjectPCM"
ACCID = None

_pending = {}
_pending_lock = threading.Lock()
_notify_cbs = {}

ws_client = None
_accid_event = threading.Event()


# ============================================================================
# WebSocket infrastructure
# ============================================================================

def generate_guid():
    return str(uuid.uuid4())


def send_request(title, data=None, timeout=10):
    global ACCID
    guid = generate_guid()
    msg = {
        "accid": ACCID or "",
        "title": title,
        "timestamp": int(time.time() * 1000),
        "guid": guid,
        "data": data or {},
    }
    evt = threading.Event()
    holder = {"resp": None}
    with _pending_lock:
        _pending[guid] = (evt, holder)

    ws_client.send(json.dumps(msg))

    if not evt.wait(timeout):
        with _pending_lock:
            _pending.pop(guid, None)
        raise TimeoutError("Request %s timed out after %ds" % (title, timeout))

    with _pending_lock:
        _pending.pop(guid, None)
    return holder["resp"] or {}


def on_ws_message(ws, message):
    global ACCID
    try:
        root = json.loads(message)
    except json.JSONDecodeError:
        return
    title = root.get("title", "")

    if root.get("accid"):
        ACCID = root.get("accid")
        _accid_event.set()

    if title.startswith("response_"):
        guid = root.get("guid", "")
        with _pending_lock:
            entry = _pending.get(guid)
        if entry:
            evt, holder = entry
            holder["resp"] = root.get("data", {})
            evt.set()
    elif title.startswith("notify_"):
        cb = _notify_cbs.get(title)
        if cb:
            try:
                cb(root.get("data", {}))
            except Exception as e:
                print("\n[%s] Notify callback error: %s" % (TAG, e))


def on_ws_open(ws):
    print("[%s] WebSocket connected." % TAG)


def on_ws_close(ws, code, msg):
    print("[%s] WebSocket closed (code=%s)." % (TAG, code))


def on_ws_error(ws, error):
    print("[%s] WebSocket error: %s" % (TAG, error))


def connect_ws(host, port, timeout=10):
    global ws_client
    ready = threading.Event()

    def _on_open(ws):
        on_ws_open(ws)
        ready.set()

    ws_client = websocket.WebSocketApp(
        "ws://%s:%d" % (host, port),
        on_open=_on_open,
        on_message=on_ws_message,
        on_close=on_ws_close,
        on_error=on_ws_error,
    )

    ws_thread = threading.Thread(target=ws_client.run_forever, daemon=True)
    ws_thread.start()

    print("[%s] Connecting to %s:%d ..." % (TAG, host, port))
    if not ready.wait(timeout=timeout):
        print("[%s] Connection timeout!" % TAG)
        sys.exit(1)

    print("[%s] Waiting for ACCID ..." % TAG)
    if not _accid_event.wait(timeout=timeout):
        print("[%s] ACCID not received, using empty string." % TAG)
    else:
        print("[%s] ACCID: %s" % (TAG, ACCID))


# ============================================================================
# PCM utilities
# ============================================================================

def generate_sine_pcm(freq, duration, sample_rate=16000):
    n = int(sample_rate * duration)
    t = np.arange(n, dtype=np.float64) / sample_rate
    return (32767 * 0.8 * np.sin(2 * np.pi * freq * t)).astype(np.int16)


def load_wav_pcm(wav_path):
    import wave
    with wave.open(wav_path, "rb") as wf:
        if wf.getsampwidth() != 2:
            raise ValueError("Only 16-bit WAV supported, got %d-bit" % (wf.getsampwidth() * 8))
        sr = wf.getframerate()
        ch = wf.getnchannels()
        pcm_bytes = wf.readframes(wf.getnframes())
    return np.frombuffer(pcm_bytes, dtype=np.int16), sr, ch


def write_wav(filepath, pcm_int16_array, sample_rate, channels, bits_per_sample=16):
    data_bytes = pcm_int16_array.astype(np.int16).tobytes()
    num_samples = len(pcm_int16_array)
    data_size = len(data_bytes)
    byte_rate = sample_rate * channels * (bits_per_sample // 8)
    block_align = channels * (bits_per_sample // 8)

    with open(filepath, "wb") as f:
        f.write(b"RIFF")
        f.write(struct.pack("<I", 4 + (8 + 16) + (8 + data_size)))
        f.write(b"WAVE")
        f.write(b"fmt ")
        f.write(struct.pack("<I", 16))
        f.write(struct.pack("<HHIIHH", 1, channels, sample_rate,
                            byte_rate, block_align, bits_per_sample))
        f.write(b"data")
        f.write(struct.pack("<I", data_size))
        f.write(data_bytes)

    duration = num_samples / max(sample_rate * channels, 1)
    print("[%s] Saved %s (%d samples, %.1fs)" % (TAG, filepath, num_samples, duration))


def pcm_rms_db(samples_int16):
    if len(samples_int16) == 0:
        return -96
    rms = np.sqrt(np.mean(samples_int16.astype(np.float64) ** 2))
    return int(20 * math.log10(rms / 32768.0)) if rms > 0 else -96


def encode_samples(samples_int16, fmt):
    """Encode int16 numpy array to the chosen wire format."""
    if fmt == "base64":
        return base64.b64encode(samples_int16.tobytes()).decode("ascii")
    else:
        return samples_int16.tolist()


def decode_samples(samples_val):
    """Decode samples from either int16 JSON array or base64 string -> numpy int16 array."""
    if isinstance(samples_val, list):
        return np.array(samples_val, dtype=np.int16)
    elif isinstance(samples_val, str):
        return np.frombuffer(base64.b64decode(samples_val), dtype=np.int16)
    return np.array([], dtype=np.int16)


# ============================================================================
# Inject
# ============================================================================

def run_inject(args):
    if args.wav:
        samples, sample_rate, channels = load_wav_pcm(args.wav)
        print("[%s] Loaded WAV: %s" % (TAG, args.wav))
    else:
        sample_rate = args.sample_rate
        channels = 1
        samples = generate_sine_pcm(args.freq, args.duration, sample_rate)
        print("[%s] Generated sine: %.0fHz, %.1fs" % (TAG, args.freq, args.duration))

    num_samples = len(samples)
    rms = pcm_rms_db(samples)
    encoded = encode_samples(samples, args.format)

    if args.format == "base64":
        payload_size = len(encoded)
    else:
        payload_size = len(json.dumps(encoded))
    raw_size = num_samples * 2

    print("[%s] PCM: %d samples, %d raw bytes, RMS: %d dB" % (TAG, num_samples, raw_size, rms))
    print("[%s] Format: %s, payload: %d bytes" % (TAG, args.format, payload_size))

    connect_ws(args.host, args.port)

    print("[%s] Sending request_audio_inject_pcm ..." % TAG)
    try:
        resp = send_request("request_audio_inject_pcm", {
            "sample_rate": sample_rate,
            "channels": channels,
            "samples": encoded,
        }, timeout=10)
        result = resp.get("result", "unknown")
        print("[%s] Result: %s" % (TAG, result))
        if result != "success":
            print("[%s] Response: %s" % (TAG, json.dumps(resp, indent=2, ensure_ascii=False)))
    except TimeoutError as e:
        print("[%s] %s" % (TAG, e))
    finally:
        ws_client.close()


# ============================================================================
# Listen for broadcasts
# ============================================================================

def run_listen(args):
    connect_ws(args.host, args.port)

    received_chunks = []
    chunk_lock = threading.Lock()
    chunk_info = {"sample_rate": 16000, "channels": 1}
    count = [0]
    stop_event = threading.Event()

    def on_notify(data):
        chunk_info["sample_rate"] = data.get("sample_rate", 16000)
        chunk_info["channels"] = data.get("channels", 1)
        samples_val = data.get("samples")
        if samples_val is None:
            return

        samples = decode_samples(samples_val)
        if len(samples) == 0:
            return

        fmt = "base64" if isinstance(samples_val, str) else "int16[]"
        count[0] += 1
        with chunk_lock:
            received_chunks.append(samples)
        rms = pcm_rms_db(samples)
        print("\r[%s] #%d: %d samples, rate=%d, ch=%d, RMS=%d dB, fmt=%s   " %
              (TAG, count[0], len(samples),
               chunk_info["sample_rate"], chunk_info["channels"], rms, fmt), end="")
        sys.stdout.flush()

    def _save_and_exit():
        _notify_cbs.pop("notify_audio_inject_pcm", None)
        print("\n[%s] Stopped. Received %d broadcasts." % (TAG, count[0]))
        with chunk_lock:
            chunks = list(received_chunks)
        if chunks and args.output:
            all_pcm = np.concatenate(chunks)
            write_wav(args.output, all_pcm,
                      chunk_info["sample_rate"], chunk_info["channels"])
        elif not chunks:
            print("[%s] No audio data received!" % TAG)
        ws_client.close()

    def _signal_handler(signum, frame):
        stop_event.set()

    _notify_cbs["notify_audio_inject_pcm"] = on_notify
    signal.signal(signal.SIGINT, _signal_handler)
    signal.signal(signal.SIGTERM, _signal_handler)

    print("[%s] Listening for notify_audio_inject_pcm ... (Ctrl+C to stop)" % TAG)
    try:
        while not stop_event.is_set():
            stop_event.wait(0.5)
    except KeyboardInterrupt:
        pass

    _save_and_exit()


# ============================================================================
# Main
# ============================================================================

def main():
    parser = argparse.ArgumentParser(
        description="Audio PCM inject test tool (WebSocket)",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Examples:
  %(prog)s --host 10.192.1.2                              # Inject 1s 440Hz (int16[])
  %(prog)s --host 10.192.1.2 --format base64              # Inject 1s 440Hz (base64)
  %(prog)s --host 10.192.1.2 --wav hello.wav              # Inject from WAV
  %(prog)s --host 10.192.1.2 --listen -o out.wav          # Listen broadcasts
  %(prog)s --host 10.192.1.2 --freq 880 -d 2              # Inject 2s 880Hz
""")
    parser.add_argument("--host", default="10.192.1.2",
                        help="WebSocket server address (default: 10.192.1.2)")
    parser.add_argument("--port", type=int, default=5000,
                        help="WebSocket port (default: 5000)")
    parser.add_argument("--sample-rate", type=int, default=16000,
                        help="Sample rate in Hz (default: 16000)")
    parser.add_argument("--freq", type=float, default=440.0,
                        help="Sine wave frequency in Hz (default: 440)")
    parser.add_argument("-d", "--duration", type=float, default=1.0,
                        help="Duration in seconds (default: 1.0)")
    parser.add_argument("--wav", type=str,
                        help="Load PCM from WAV file instead of generating sine")
    parser.add_argument("-o", "--output", type=str,
                        help="Output WAV path (for --listen)")
    parser.add_argument("--format", choices=["int16", "base64"], default="int16",
                        help="samples encoding format (default: int16)")

    parser.add_argument("--listen", action="store_true",
                        help="Listen for notify_audio_inject_pcm broadcasts")

    args = parser.parse_args()

    print("[%s] ==========================================" % TAG)
    print("[%s]  Audio PCM Inject Test" % TAG)
    print("[%s] ==========================================" % TAG)

    if args.listen:
        run_listen(args)
    else:
        run_inject(args)

    print("[%s] Done." % TAG)


if __name__ == "__main__":
    main()
```

## 3.7 全局消息协议接口

### 3.7.1 机器人状态信息

此协议将定时上报机器人状态信息。

| 上报状态信息 | 描述                             |
| ------------ | -------------------------------- |
| `accid`      | 机器人序列号                     |
| `title`      | notify_robot_info                |
| `timestamp`  | 消息发出时间戳，单位为毫秒       |
| `guid`       | 消息的 guid 值，唯一标识这条消息 |
| `data`       | 存放消息内容                     |

**示例：**

```json
{
  "accid": "HU_D04_01_001", 
  "title": "notify_robot_info", 
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": []
  }
}
```

#### 3.7.1.1 电池数据

```json
{
  "accid": "HU_D04_01_001", 
  "title": "notify_robot_info", 
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": [
        ......
        {
                "level": 0,
                "name": "peripheral",
                "message": "OK",
                "hardware_id": "peripheral",
                "values": [
                    {
                        "key": "bmsconn",
                        "value": "ON"
                    },
                    {
                        "key": "bat_chg",
                        "value": "OFF"
                    },
                    {
                        "key": "bat_off",
                        "value": "OFF"
                    },
                    {
                        "key": "bat_prt",
                        "value": "0"
                    },
                    {
                        "key": "bat_vol",
                        "value": "48830"
                    },
                    {
                        "key": "bat_cur",
                        "value": "2870"
                    },
                    {
                        "key": "battery",
                        "value": "29"
                    },
                    {
                        "key": "bat_temp0",
                        "value": "430"
                    },
                    {
                        "key": "bat_temp2",
                        "value": "430"
                    },
                    {
                        "key": "bat_temp4",
                        "value": "400"
                    },
                    {
                        "key": "battery_capacity",
                        "value": "9000mAh"
                    }
                ]
            },
    ]
  }
}
```

| 字段      | 含义                                          |
| --------- | --------------------------------------------- |
| bmsconn   | 电池连接状态 ：【OFF：未连接，ON：已连接】    |
| bat_chg   | 电池充电器状态 ：【OFF：未连接，ON：已连接】  |
| bat_off   | 电池预关机状态 ：【OFF：1s 后断电，ON：正常】 |
| bat_prt   | 电池故障码：【 0：正常， 非 0：异常】         |
| bat_vol   | 电池实时电压 单位：mV                         |
| bat_cur   | 电池实时电流 单位：mA                         |
| battery   | 电池电量百分比 0~100                          |
| bat_temp0 | 电池温度 0~100 单位：x10℃                    |
| bat_temp2 | 电池温度 0~100 单位：x10℃                    |
| bat_temp4 | 电池温度 0~100 单位：x10℃                    |

#### 3.7.1.2 系统信息

```json
{
  "accid": "HU_D04_01_001", 
  "title": "notify_robot_info", 
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": [
          {
              "level": 0,
              "name": "system_info",
              "message": "system info",
              "hardware_id": "system_info",
              "values": [
                {
                  "key": "ability_running",
                  "value": "ZeroTorque"
                },
                {
                  "key": "ecm_version",
                  "value": "1.1.2"
                },
                {
                  "key": "mode",
                  "value": "Remote"
                },
                {
                  "key": "motor_version",
                  "value": "1: 0.0.9; 2: 0.0.9; 3: 0.0.9; 4: 0.0.9; 5: 0.0.9; 6: 0.0.9; 7: 0.0.9; 8: 0.0.9; 9: 0.0.9; 10: 0.0.9; 11: 0.0.9; 12: 0.0.9; 13: 0.0.9; 14: 0.0.9; 15: 0.0.9; 16: 0.0.9; "
                },
                {
                  "key": "pms_version",
                  "value": "2.1.8"
                },
                {
                  "key": "robot_status",
                  "value": "ZeroTorque"
                },
                {
                  "key": "version",
                  "value": "robot-hu-d-2.1.0.20251225062343"
                },
                {
                  "key": "sn",
                  "value": "HU_D04_01_131"
                }
              ]
        }
    ]
  }
}
```

| **字段**        | **含义**               |
| --------------- | ---------------------- |
| version         | 主控版本               |
| ecm_version     | 主站版本               |
| pms_version     | 分电板版本             |
| motor_version   | 电机版本               |
| sn              | 机器人序列号           |
| robot_status    | 机器人当前状态         |
| ability_running | 机器人当前运行的控制器 |

#### 3.7.1.3 电机状态信息

```json
{
  "accid": "HU_D04_01_001", 
  "title": "notify_robot_info", 
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": [
          {
                "level": 1,
                "name": "ethercatCommunicationExp",
                "message": "WARN",
                "hardware_id": "ethercat",
                "values": [
                    {
                        "key": "ethercatCommunicationExp",
                        "value": "motor 17 MOTOR_LOST triggered HALF_STAND"
                    },
                    {
                        "key": "ethercatResetNormal",
                        "value": "ok!"
                    }
                ]
          }
    ]
  }
}
```

| 字段        | 含义                            |
| ----------- | ------------------------------- |
| level       | 异常等级[0:ok  1:warn  2:error] |
| name        | 异常类型                        |
| message     | 等级字符串                      |
| hardware_id | 硬件 id                         |
| values      | 该硬件的所有异常集合            |

### 3.7.2 遥控器数据

此协议将上报机器人遥控器数据。

| 上报数据信息 | 描述                             |
| ------------ | -------------------------------- |
| `accid`      | 机器人序列号                     |
| `title`      | notify_joy_data                  |
| `timestamp`  | 消息发出时间戳，单位为毫秒       |
| `guid`       | 消息的 guid 值，唯一标识这条消息 |
| `data`       | 存放消息内容                     |

**示例：**

```json
{
  "accid": "HU_D04_01_001", 
  "title": "notify_joy_data", 
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "axes": [],     # 遥感数据
    "buttons": []   # 按键数据
  }
}
```

## 3.8 协议接口调用示例

### 3.8.1 Python 示例

- **环境准备：** 以 Ubuntu 20.04 系统为例，安装下面依赖

```bash
sudo apt install python3-dev python3-pip
sudo pip install websocket-client==1.8.0
```

- **运行脚本**

```bash
python humanoid.py
```

- **humanoid.py 实现**
  - ACCID：替换为真实的软件 SN
  - ROBOT_IP: 一般情况，仿真为 127.0.0.1，真机为 10.192.1.2

```python
import json
import uuid
import threading
import time
import websocket
from datetime import datetime

# Replace this ACCID value with your robot's actual serial number (SN)
ACCID = None

# Replace it with the real IP address of the robot. 
# Usually, for simulation, it is: 127.0.0.1
# for a real machine, it is: 10.192.1.2
ROBOT_IP = "10.192.1.2"

# Atomic flag for graceful exit
should_exit = False

# WebSocket client instance
ws_client = None

# Generate dynamic GUID
def generate_guid():
    return str(uuid.uuid4())

# Send WebSocket request with title and data
def send_request(title, data=None):
    global ACCID
    if data is None:
        data = {}
    
    # Create message structure with necessary fields
    message = {
        "accid": ACCID,
        "title": title,
        "timestamp": int(time.time() * 1000),  # Current timestamp in milliseconds
        "guid": generate_guid(),
        "data": data
    }

    message_str = json.dumps(message)
    
    # Send the message through WebSocket if client is connected
    if ws_client:
        ws_client.send(message_str)

# Handle user commands
def handle_commands():
    global should_exit
    while not should_exit:
        command = input("Enter command ('prepare', 'servo', 'movej', 'movel', 'movep', 'head', 'waist', 'state', 'claw_cmd', 'claw_state', 'damping', 'zero') or 'exit' to quit:\n")
        
        if command == "exit":
            should_exit = True  # Set exit flag to stop the loop
            break
        elif command == "prepare":
            send_request("request_prepare")  # request_prepare
        elif command == "servo":
            # Servo control mode flag from user
            mode_input = input("Enable mode (0/1/2):").strip()
            mode_value = int(mode_input) if mode_input in ('0','1','2') else 0
            send_request("request_set_move_mode", {"mode": mode_value})
        elif command == "movej":
            send_request("request_moveJ", { # request_moveJ
              "left": [-1.44532, 0.0987686, 0.179059, -1.64716, -0.0537614, 0.200834, -0.236136],
              "right": [0.10103,-0.0987769,-0.179462,-1.64705,0.0527488,0.198867,0.235933],
              "speed": 0.2
            }) 
        elif command == "movep":
            send_request("request_moveP", { # request_moveP
              "left_position": [0.089644,0.428712,0.0519788],
              "left_quat": [0.269296,-0.119683,-0.489868,0.820478],
              "right_position": [0.0835307,-0.531453,0.13568],
              "right_quat": [-0.436152,-0.285065,0.265969,0.81103],
              "speed": 0.1
            })
        elif command == "head":
            send_request("request_moveJ", { # request_moveJ
              "head_pitch": 0.5854,
              "head_yaw": 0.5854,
              "speed": 0.1
            })
        elif command == "waist":
            send_request("request_moveJ", { # request_set_waist_and_height
              "torso_height": 0.0,
              "torso_pitch": 0.0,
              "torso_roll": 0.0,
              "torso_yaw": 0.0
            })
        elif command == "claw_cmd":
            send_request("request_set_claw_cmd", { # request_set_claw_cmd
              "left_opening": 100,
              "left_speed": 500, 
              "left_force": 500,
              "left_mode": 1,
              "right_opening": 100,
              "right_speed": 500,
              "right_force": 500,
              "right_mode": 1
            })
        elif command == "claw_state":
            send_request("request_get_claw_state")
        elif command == "state":
            send_request("request_get_move_pose")  # request_get_move_pose
        elif command == "damping":
            send_request("request_damping")  # request_damping
        elif command == "zero":
            send_request("request_zero_torque")  # request_zero_torque

# WebSocket on_open callback
def on_open(ws):
    print("Connected!")
    # Start handling commands in a separate thread
    threading.Thread(target=handle_commands, daemon=True).start()

# WebSocket on_message callback
def on_message(ws, message):
    global ACCID
    root = json.loads(message)
    title = root.get("title", "")
    ACCID = root.get("accid", None)

    if title != "notify_robot_info":
        print(f"Received message: {message}")  # Print the received message

# WebSocket on_close callback
def on_close(ws, close_status_code, close_msg):
    print("Connection closed.")

# Close WebSocket connection
def close_connection(ws):
    ws.close()

def main():
    global ws_client
    
    # Create WebSocket client instance
    ws_client = websocket.WebSocketApp(
        f"ws://{ROBOT_IP}:5000",  # WebSocket server URI
        on_open=on_open,
        on_message=on_message,
        on_close=on_close
    )
    
    # Configure socket send and receive buffer sizes
    # Increase send buffer size to 2MB (default is typically much smaller)
    # This helps prevent data loss when sending large messages or high-frequency data
    ws_client.sock_opt = [("socket", "SO_SNDBUF", 2 * 1024 * 1024)]
    
    # Increase receive buffer size to 2MB
    # This allows handling larger incoming messages without truncation
    ws_client.sock_opt.append(("socket", "SO_RCVBUF", 2 * 1024 * 1024))
    
    # Run WebSocket client loop
    print("Press Ctrl+C to exit.")
    ws_client.run_forever()

if __name__ == "__main__":
    main()

```

### 3.8.2 Linux C++ 示例

- **环境准备：** 以 Ubuntu 20.04 系统为例，安装 websocketpp、nlohmann/json 和 boost 依赖：

```bash
sudo apt-get install libboost-all-dev libwebsocketpp-dev nlohmann-json3-dev
```

- **编译代码**

```bash
g++ -std=c++11 humanoid humanoid.cpp -o humanoid humanoid -lssl -lcrypto -lboost_system -lpthread
```

- **运行程序**

```bash
./humanoid
```

- **humanoid.cpp 实现**

```cpp
#include <iostream>
#include <atomic>
#include <string>
#include <thread>
#include <chrono>
#include <websocketpp/client.hpp>
#include <websocketpp/config/asio.hpp>
#include <nlohmann/json.hpp>
#include <boost/uuid/uuid.hpp>
#include <boost/uuid/uuid_generators.hpp>
#include <boost/uuid/uuid_io.hpp>

using json = nlohmann::json;
using websocketpp::client;
using websocketpp::connection_hdl;

// Replace this value with the actual serial number (SN) of the robot.
static std::string ACCID = "";

// Replace it with the real IP address of the robot.
// Usually, for simulation, it is: 127.0.0.1
// for a real machine, it is: 10.192.1.2
const std::string ROBOT_IP = "10.192.1.2";

// WebSocket client instance
static client<websocketpp::config::asio> ws_client;

// Atomic flag for graceful exit
static std::atomic<bool> should_exit(false);

// Connection handle for sending messages
static connection_hdl current_hdl;

// Generate dynamic GUID
static std::string generate_guid() {
  boost::uuids::random_generator gen;
  boost::uuids::uuid u = gen();
  return boost::uuids::to_string(u);
}

// Send WebSocket request with title and data
static void send_request(const std::string& title, const json& data = json::object()) {
  json message;
  
  // Adding necessary fields to the message
  message["accid"] = ACCID;
  message["title"] = title;
  message["timestamp"] = std::chrono::duration_cast<std::chrono::milliseconds>(
                              std::chrono::system_clock::now().time_since_epoch()).count();
  message["guid"] = generate_guid();
  message["data"] = data;

  std::string message_str = message.dump();
  
  // Send the message through WebSocket
  ws_client.send(current_hdl, message_str, websocketpp::frame::opcode::text);
}

// Handle user commands
void handle_commands() {
  std::cout << "Enter command ('prepare', 'servo', 'movej', 'movel', 'movep', 'head', 'state', 'waist', 'claw_cmd', 'claw_state', 'damping', 'zero') or 'exit' to quit:\n";
  while (!should_exit) {
      std::string command;
      std::cin >> command;

      if (command == "exit") {
          should_exit = true;
          return;
      } else if (command == "prepare") {
          send_request("request_prepare");
      } else if (command == "servo") {
          int mode_value;
          std::cout << "Enable mode (0/1/2): ";
          if (!(std::cin >> mode_value)) {
              std::cerr << "Error: Invalid input. Please enter 0, 1, or 2." << std::endl;
              return;
          }
          if (mode_value < 0 || mode_value > 2) {
              std::cerr << "Error: Invalid input. Please enter 0, 1, or 2." << std::endl;
              return;
          }
          
          nlohmann::json data = {{"mode", mode_value}};
          send_request("request_set_move_mode", data);
      } else if (command == "movej") {
          nlohmann::json data = {
              {"left", {-1.44532, 0.0987686, 0.179059, -1.64716, -0.0537614, 0.200834, -0.236136}},
              {"right", {0.10103,-0.0987769,-0.179462,-1.64705,0.0527488,0.198867,0.235933}},
              {"speed", 0.2}
          };
          send_request("request_moveJ", data);
      } else if (command == "movep") {
          nlohmann::json data = {
              {"left_position", {0.089644,0.428712,0.0519788}},
              {"left_quat", {0.269296,-0.119683,-0.489868,0.820478}},
              {"right_position", {0.0835307,-0.531453,0.13568}},
              {"right_quat", {-0.436152,-0.285065,0.265969,0.81103}},
              {"speed", 0.1}
          };
          send_request("request_moveP", data);
      } else if (command == "head") {
          nlohmann::json data = {
              {"head_yaw", 0.5854},
              {"head_pitch", 0.5854},
              {"speed", 0.1}
          };
          send_request("request_moveJ", data);
      } else if (command == "waist") {
          nlohmann::json data = {
              {"torso_height", 0.0},
              {"torso_pitch", 0.0},
              {"torso_roll", 0.0},
              {"torso_yaw", 0.0}
          };
          send_request("request_moveJ", data);
      } else if (command == "claw_cmd") {
          nlohmann::json data = {
              {"left_opening", 100},
              {"left_speed", 500},
              {"left_force", 500},
              {"left_mode", 1},
              {"right_opening", 100},
              {"right_speed", 500},
              {"right_force", 500},
              {"right_mode", 1}
          };
          send_request("request_set_claw_cmd", data);
      } else if (command == "claw_state") {
          send_request("request_get_claw_state");
      } else if (command == "state") {
          send_request("request_get_move_pose");
      } else if (command == "damping") {
          send_request("request_damping");
      } else if (command == "zero") {
          send_request("request_zero_torque");
      }

      sleep(1);

      std::cout << "\nEnter command ('prepare', 'servo', 'movej', 'movel', 'movep', 'servop', 'head', 'waist', 'state', 'damping', 'zero') or 'exit' to quit:\n";
  }
}

// WebSocket open callback
static void on_open(connection_hdl hdl) {
  std::cout << "Connected!" << std::endl;
  
  // Save connection handle for sending messages later
  current_hdl = hdl;

  // Start handling commands in a separate thread
  std::thread(handle_commands).detach();
}

// WebSocket TCP initialization handler
static void on_tcp_init(connection_hdl hdl)
{
  auto con = ws_client.get_con_from_hdl(hdl);

  // Obtain the underlying TCP socket
  auto& socket = con->get_socket().lowest_layer();

  // Configure socket options
  try {
    boost::system::error_code ec;
    
    // Set send buffer size (e.g., 2MB)
    const size_t sendBufferSize = 2 * 1024 * 1024;
    socket.set_option(websocketpp::lib::asio::socket_base::send_buffer_size(sendBufferSize), ec);
    
    if (ec)
    {
      printf("Failed to set send buffer size: %s", ec.message().c_str());
    }

    // Set receive buffer size (e.g., 2MB)
    const size_t recvBufferSize = 2 * 1024 * 1024;
    socket.set_option(websocketpp::lib::asio::socket_base::receive_buffer_size(recvBufferSize), ec);

    if (ec)
    {
      printf("Failed to set receive buffer size: %s", ec.message().c_str());
    }

    // Disable Nagle's algorithm to reduce latency
    socket.set_option(websocketpp::lib::asio::ip::tcp::no_delay(true), ec);
    
    if (ec)
    {
      printf("Failed to disable Nagle's algorithm: %s", ec.message().c_str());
    }
  } catch (const std::exception& e) {
    printf("Socket configuration exception: %s", e.what());
  }
}

// WebSocket message callback
static void on_message(connection_hdl hdl, client<websocketpp::config::asio>::message_ptr msg) {
  // Parse JSON data from message payload
  json data = json::parse(msg->get_payload());
        
  // Extract 'accid' field if present
  if (data.contains("accid") && data["accid"].is_string() && ACCID.empty()) {
      ACCID = data["accid"].get<std::string>();
  }

  if (msg->get_payload().find("notify_robot_info") == std::string::npos) {
      std::cout << "Received message: " << msg->get_payload() << std::endl;
  }
}

// WebSocket close callback
static void on_close(connection_hdl hdl) {
  std::cout << "Connection closed." << std::endl;
}

// Close WebSocket connection
static void close_connection(connection_hdl hdl) {
  ws_client.close(hdl, websocketpp::close::status::normal, "Normal closure");  // Close connection normally
}

int main() {
  ws_client.init_asio();  // Initialize ASIO for WebSocket client

  ws_client.set_access_channels(websocketpp::log::alevel::none);
  
  // Set WebSocket event handlers
  ws_client.set_open_handler(&on_open);  // Set open handler
  ws_client.set_message_handler(&on_message);  // Set message handler
  ws_client.set_close_handler(&on_close);  // Set close handler
  ws_client.set_tcp_init_handler(&on_tcp_init); // Set tcp init handler

  std::string server_uri = "ws://" + ROBOT_IP + ":5000";  // WebSocket server URI

  websocketpp::lib::error_code ec;
  client<websocketpp::config::asio>::connection_ptr con = ws_client.get_connection(server_uri, ec);  // Get connection pointer

  if (ec) {
      std::cout << "Error: " << ec.message() << std::endl;
      return 1;  // Exit if connection error occurs
  }

  connection_hdl hdl = con->get_handle();  // Get connection handle
  ws_client.connect(con);  // Connect to server
  std::cout << "Press Ctrl+C to exit." << std::endl;
  
  // Run the WebSocket client loop
  ws_client.run();

  return 0;
}

```



### 3.8.3 JavaScript 示例

- **运行 humanoid.html：** 将 humanoid.html 文件保存到电脑中，然后在浏览器中打开 humanoid.html 运行。

![图片](data:image/webp;base64,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)

- **humanoid.html 实现**

```html
<!DOCTYPE html>

<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>WebSocket Robot Control</title>
    <style>
        #commandInput {
            width: 700px; 
            padding: 10px;
            font-size: 14px;
        }
    </style>
</head>
<body>
    <h2>Dual ARM Commands</h2>
    <input type="text" id="commandInput" placeholder="Enter command ('prepare', 'servo', 'movej', 'movel', 'movep', 'head', 'waist', 'claw_cmd', 'claw_state', 'state', 'damping', 'zero', 'exit')">
    <p>Type a command and press Enter.</p>

    <script>
        // Replace this ACCID value with your robot's actual serial number (SN)
        let ACCID = "";

        // WebSocket client instance
        let wsClient = null;

        // Generate dynamic GUID
        function generateGuid() {
            return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, function(c) {
                const r = Math.random() * 16 | 0,
                      v = c === 'x' ? r : (r & 0x3 | 0x8);
                return v.toString(16);
            });
        }

        // Send WebSocket request with title and data
        function sendRequest(title, data = {}) {
            const message = {
                accid: ACCID,
                title: title,
                timestamp: Date.now(),
                guid: generateGuid(),
                data: data
            };

            if (wsClient && wsClient.readyState === WebSocket.OPEN) {
                wsClient.send(JSON.stringify(message));
            }
        }

        // Handle user commands
        function handleCommands() {
            const commandInput = document.getElementById('commandInput');
            commandInput.addEventListener('keydown', function(event) {
                if (event.key === 'Enter') {
                    const command = commandInput.value.trim();
                    commandInput.value = '';

                    switch (command) {
                        case 'prepare':
                            sendRequest('request_prepare');
                            break;
                        case 'servo':
                            const modeInput = prompt("Enable Servo (0/1/2):").trim();
                            let modeValue = 0;
                            
                            // 尝试把输入解析为整数
                            const n = parseInt(modeInput, 10);
                            if (!Number.isNaN(n) && (n === 0 || n === 1 || n === 2)) {
                                modeValue = n;
                            } else {
                                // 非法输入,给出错误并返回
                                alert("Error: Invalid input. Please enter 0, 1, or 2.");
                                return;
                            }
                            sendRequest('request_set_move_mode', { mode: modeValue });
                            break;
                        case 'movej':
                            sendRequest('request_moveJ', {
                                left: [-1.44532, 0.0987686, 0.179059, -1.64716, -0.0537614, 0.200834, -0.236136],
                                right: [0.10103,-0.0987769,-0.179462,-1.64705,0.0527488,0.198867,0.235933],
                                speed: 0.2
                            });
                            break;
                        case 'movep':
                            sendRequest('request_moveP', {
                                left_position: [0.089644,0.428712,0.0519788],
                                left_quat: [0.269296,-0.119683,-0.489868,0.820478],
                                right_position: [0.0835307,-0.531453,0.13568],
                                right_quat: [-0.436152,-0.285065,0.265969,0.81103],
                                speed: 0.1
                            });
                            break;
                        case 'head':
                            sendRequest('request_moveJ', {
                                head_yaw: 0.5854,
                                head_pitch: 0.5854,
                                speed: 0.1
                            });
                            break;
                        case 'waist':
                            sendRequest('request_moveJ', {
                                torso_height: 0.0,
                                torso_pitch: 0.0,
                                torso_roll: 0.0,
                                torso_yaw: 0.0
                            });
                            break;
                        case 'claw_cmd':
                            sendRequest('request_set_claw_cmd', {
                                left_opening: 100,
                                left_speed: 500,
                                left_force: 500,
                                left_mode: 1,
                                right_opening: 100,
                                right_speed: 500,
                                right_force: 500,
                                right_mode: 1
                            });
                            break;
                        case 'claw_state':
                            sendRequest('request_get_claw_state');
                            break;
                        case 'state':
                            sendRequest('request_get_move_pose');
                            break;
                        case 'damping':
                            sendRequest('request_damping');
                            break;
                        case 'zero':
                            sendRequest('request_zero_torque');
                            break;
                        case 'exit':
                            wsClient.close();
                            break;
                        default:
                            alert("Invalid command. Try again.");
                    }
                }
            });
        }

        // WebSocket onOpen callback
        function onOpen() {
            console.log("Connected!");
            handleCommands();
        }

        // WebSocket onMessage callback
        function onMessage(event) {
            try {
                const message = JSON.parse(event.data);

                // Dynamically set ACCID from message if not already set
                if (!ACCID && message.accid) {
                    ACCID = message.accid;
                    console.log(`ACCID set to: ${ACCID}`);
                }
            } catch (error) {
                console.log("Failed to parse message:", error);
            }
            
            if (event.data.includes('notify_robot_info')) return;
            console.log("Received message:", event.data);
        }

        // WebSocket onClose callback
        function onClose(event) {
            console.log("Connection closed.");
        }

        // Initialize WebSocket client
        function initWebSocket() {
            // Replace it with the real IP address of the robot.
            // Usually, for simulation, it is: 127.0.0.1
            // for a real machine, it is: 10.192.1.2
            wsClient = new WebSocket('ws://10.192.1.2:5000');
            wsClient.onopen = onOpen;
            wsClient.onmessage = onMessage;
            wsClient.onclose = onClose;
            console.log("Press Ctrl+C to exit.");
        }

        // Start WebSocket connection when the page loads
        window.onload = initWebSocket;
    </script>
</body>
</html>
```

# 4 底层运动控制开发接口

**跨平台底层运动控制开发接口库**提供统一的 C++/Python API，兼容 ROS1、ROS2 及非 ROS 系统，实现运动控制算法的快速移植与部署。通过硬件抽象层和标准化通信协议，开发者可无缝切换仿真与真实硬件环境，显著降低多平台适配成本。

> **注意：**
>
> 1. 使用底层控制开发接口时，需通过按键 `R1+START` 切换**开发者模式**，此时高层开发接口会被禁用，机器人只响应上下电和校零遥控器指令。
> 2. 底层接口代码调用示例可参考 RL 部署训练。
> 3. 切换到开发者模式后，掉电模式会保留，退出开发者模式按键：`L2+○`

## 4.1 C++ 运动控制开发接口

### 4.1.1 getInstance 接口

| 函数名   | getInstance                                              |
| -------- | -------------------------------------------------------- |
| 函数原型 | static Humanoid* getInstance();                          |
| 功能概述 | 获取 Humanoid 机器人类单例实例的指针                     |
| 参数     | 无                                                       |
| 返回值   | Humanoid*，指向 Humanoid 实例的指针                      |
| 备注     | 使用了单例模式，确保 Humanoid 类只有一个实例存在于程序中 |

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  
  return 0;
}
```

### 4.1.2 init 接口

| 函数名   | init                                                                                                                                   |
| -------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| 函数原型 | bool init(const std::string& robot_ip_address = "127.0.0.1");                                                                         |
| 功能概述 | 初始化运动控制算法程序的通信运行环境，通常在主函数中调用其它接口之前调用，完成初始化工作。                                             |
| 参数     | robot_ip_address：机器人的 IP 地址。对于仿真，通常设置为 "127.0.0.1"，而对于真实机器人，可能设置为 "10.192.1.2"。                     |
| 返回值   | 如果初始化成功，则返回 true；否则返回 false。                                                                                          |
| 备注     | 无                                                                                                                                     |

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();
  
  // 默认机器人 IP 地址
  std::string robot_ip = "127.0.0.1";
  if (argc > 1)
  {
    // 如果提供了命令行参数，则使用命令行参数作为机器人 IP 地址
    robot_ip = argv[1];
  }
  
  // 初始化运动控制算法程序的通信运行环境
  if (!robot->init(robot_ip))
  {
    // 如果初始化失败，则退出程序
    exit(1);
  }
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  return 0;
}
```

### 4.1.3 getMotorNumber 接口

| 函数名   | getMotorNumber                             |
| -------- | ------------------------------------------ |
| 函数原型 | uint32_t getMotorNumber();                 |
| 功能概述 | 获取机器人中的电机数量。                   |
| 参数     | 无                                         |
| 返回值   | 返回一个无符号整数，表示机器人中的总电机数量。 |
| 备注     | 无                                         |

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();
  
  // 默认机器人 IP 地址
  std::string robot_ip = "127.0.0.1";
  if (argc > 1)
  {
    // 如果提供了命令行参数，则使用命令行参数作为机器人 IP 地址
    robot_ip = argv[1];
  }
  
  // 初始化运动控制算法程序的通信运行环境
  if (!robot->init(robot_ip))
  {
    // 如果初始化失败，则退出程序
    exit(1);
  }
  
  // 获取机器人中的电机数量
  uint32_t motor_num = robot->getMotorNumber();
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  return 0;
}
```

### 4.1.4 subscribeImuData 接口

| 函数名   | subscribeImuData                                                       |
| -------- | ---------------------------------------------------------------------- |
| 函数原型 | void subscribeImuData(std::function<void(const ImuDataConstPtr&)> cb); |
| 功能概述 | 订阅机器人的 IMU数据，并在接收到新的 IMU 数据时调用指定的回调函数。   |
| 参数     | cb: 用于处理新 IMU 数据的回调函数。                                    |
| 返回值   | 无                                                                     |

备注：ImuData 数据结构原型如下：

```cpp
/**
 * @struct ImuData
 *
 * @brief 表示基于传感器反馈的机器人 IMU 数据的结构体。
 *
 * 此结构体封装了 IMU 数据，包括加速度计、陀螺仪和四元数。
 */
struct ImuData {
  uint64_t stamp; // 时间戳，以纳秒为单位，通常表示记录或生成此数据时的时间。
  float acc[3];   // 用于存储 IMU 加速度计数据，以跟踪沿三个轴（X、Y、Z）的线性加速度。
  float gyro[3];  // 用于存储 IMU 陀螺仪数据，以跟踪沿三个轴（X、Y、Z）的角速度或旋转速度。
  float quat[4];  // 用于存储 IMU 四元数数据，表示在三维空间中的方向（w、x、y、z）。
};

// 智能指针类型别名
typedef std::shared_ptr<ImuData> ImuDataPtr;
typedef std::shared_ptr<ImuData const> ImuDataConstPtr;
```

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();
  
  // 默认机器人 IP 地址
  std::string robot_ip = "127.0.0.1";
  if (argc > 1)
  {
    // 如果提供了命令行参数，则使用命令行参数作为机器人 IP 地址
    robot_ip = argv[1];
  }
  
  // 初始化运动控制算法程序的通信运行环境
  if (!robot->init(robot_ip))
  {
    // 如果初始化失败，则退出程序
    exit(1);
  }
  
  // 订阅机器人状态更新，并指定回调函数
  robot->subscribeImuData([&](const ImuDataConstPtr& msg) {
    // 在这里处理接收到的 ImuData 数据
    // 注意：回调函数会在收到ImuData时被调用
  });
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  return 0;
}
```

### 4.1.5 subscribeRobotState 接口

| 函数名   | subscribeRobotState                                                                              |
| -------- | ------------------------------------------------------------------------------------------------ |
| 函数原型 | void subscribeRobotState(std::function<void(const RobotStateConstPtr&)> cb);                    |
| 功能概述 | 订阅接收关于机器人状态的更新。                                                                   |
| 参数     | cb：回调函数，当接收到机器人状态更新时将被调用。回调函数参数指向 RobotState 对象的常量指针。     |
| 返回值   | 无                                                                                               |

备注：RobotState 数据结构原型如下：

```cpp
/**
 * @struct RobotState
 *
 * @brief 代表基于传感器反馈的机器人状态的结构体。
 *
 * 此结构封装了各种数据点，可用于监控和控制机器人，包括 IMU 数据（加速度计、陀螺仪、四元数）、输出扭矩、当前角度和速度等。
 */
struct RobotState {
  // 默认构造函数
  RobotState() { }
  
  // 带参数的构造函数，用于初始化向量大小为 motor_num 的 tau、q、dq 向量，初始值均为 0.0
  RobotState(int motor_num)
  : tau(motor_num, 0.0)
  , q(motor_num, 0.0)
  , dq(motor_num, 0.0)
  , motor_names(motor_num, "") { }
  
  uint64_t stamp;              // 时间戳，通常表示记录或生成这些数据的时间，以纳秒为单位
  std::vector<float> tau;      // 用于存储当前估计的输出扭矩（以牛顿米为单位）的向量
  std::vector<float> q;        // 用于存储当前角度（以弧度为单位）的向量
  std::vector<float> dq;       // 用于存储当前速度（以弧度每秒为单位）的向量
  std::vector<std::string> motor_names; // 用于存储机器人各个关节名称的向量
};

// 智能指针类型别名
typedef std::shared_ptr<RobotState> RobotStatePtr;
typedef std::shared_ptr<RobotState const> RobotStateConstPtr;
```

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();
  
  // 默认机器人 IP 地址
  std::string robot_ip = "127.0.0.1";
  if (argc > 1)
  {
    // 如果提供了命令行参数，则使用命令行参数作为机器人 IP 地址
    robot_ip = argv[1];
  }
  
  // 初始化运动控制算法程序的通信运行环境
  if (!robot->init(robot_ip))
  {
    // 如果初始化失败，则退出程序
    exit(1);
  }
  
  // 订阅机器人状态更新，并指定回调函数
  robot->subscribeRobotState([&](const RobotStateConstPtr& msg) {
    // 在这里处理接收到的 RobotState 数据
    // 注意：回调函数会在收到机器人状态更新时被调用
  });
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  return 0;
}
```

### 4.1.6 publishRobotCmd 接口

| 函数名   | publishRobotCmd                                  |
| -------- | ------------------------------------------------ |
| 函数原型 | bool publishRobotCmd(const RobotCmd& cmd);       |
| 功能概述 | 发布一个命令来控制机器人的动作。                 |
| 参数     | cmd：表示所需机器人命令的 RobotCmd 对象。        |
| 返回值   | 无                                               |

备注：RobotCmd 数据结构原型如下：

```cpp
/**
 * @struct RobotCmd
 *
 * @brief 代表控制机器人的命令的结构体。
 *
 * 这个结构体包含了可以用于控制机器人的各种命令，包括期望的工作模式、期望的角度、期望的速度、期望的输出扭矩、期望的位置刚度和期望的速度刚度。
 */
struct RobotCmd {
  RobotCmd() { }
  RobotCmd(int motor_num)
  : mode(motor_num, 0)
  , q(motor_num, 0.0)
  , dq(motor_num, 0.0)
  , tau(motor_num, 0.0)
  , Kp(motor_num, 0.0)
  , Kd(motor_num, 0.0)
  , motor_names(motor_num, "") { }
  
  uint64_t stamp;             // 时间戳（以纳秒为单位），通常表示记录或生成数据时的时间。
  std::vector<uint8_t> mode;  // 0: 力矩模式控制；1：速度模式控制；2：位置模式控制，默认设置为：0
  std::vector<float> q;       // 存储期望角度的向量（以弧度为单位）。
  std::vector<float> dq;      // 存储期望速度的向量（以弧度每秒为单位）。
  std::vector<float> tau;     // 存储期望输出扭矩的向量（以牛顿米为单位）。
  std::vector<float> Kp;      // 存储期望位置刚度的向量（以牛顿米每弧度为单位）。
  std::vector<float> Kd;      // 存储期望速度刚度的向量（以牛顿米每弧度每秒为单位）。
  std::vector<std::string> motor_names;   // 存储期望控制的机器人关节名称
};

// 智能指针类型别名
typedef std::shared_ptr<RobotCmd> RobotCmdPtr;
typedef std::shared_ptr<RobotCmd const> RobotCmdConstPtr;
```

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();
  
  // 默认机器人 IP 地址
  std::string robot_ip = "127.0.0.1";
  if (argc > 1)
  {
    // 如果提供了命令行参数，则使用命令行参数作为机器人 IP 地址
    robot_ip = argv[1];
  }
  
  // 初始化运动控制算法程序的通信运行环境
  if (!robot->init(robot_ip))
  {
    // 如果初始化失败，则退出程序
    exit(1);
  }
  
  // 获取机器人中的电机数量
  uint32_t motor_num = robot->getMotorNumber();
  
  // 创建一个包含机器人电机数量的 RobotCmd 对象
  RobotCmd cmd(motor_num);
  
  // 发布控制指令
  robot->publishRobotCmd(cmd);
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  return 0;
}
```

### 4.1.7 subscribeSensorJoy 接口

| 函数名   | subscribeSensorJoy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
| -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 函数原型 | void subscribeSensorJoy(std::function<void(const SensorJoyConstPtr&)> cb);                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| 功能概述 | 在真机部署中，该方法用于订阅来自机器人遥控器的数据。当机器人接收到遥控器的数据时，将会调用指定的回调函数，并传递包含遥控器数据的 SensorJoy 结构体常量指针给回调函数进行处理。                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
| 参数     | cb: 表示回调函数，用于接收机器人遥控器的数据。回调函数的参数类型为 SensorJoyConstPtr，即指向 SensorJoy 结构体常量的共享指针。                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| 返回值   | 无                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |

备注：SensorJoy 数据结构原型如下：

```cpp
/**
 * @struct SensorJoy
 *
 * @brief 机器人遥控器数据的结构体。
 *
 * 该结构体包含了与遥控器相关的时间戳信息，以及摇杆和按钮值。
 */
struct SensorJoy {
    uint64_t stamp;                     // 与传感器输入相关的时间戳，单位为纳秒。
    std::vector<float> axes;            // 表示操纵摇杆的值。
    std::vector<int32_t> buttons;       // 表示操纵按钮状态的值。
};       

// SensorJoy 智能指针类型的定义
typedef std::shared_ptr<SensorJoy> SensorJoyPtr;
typedef std::shared_ptr<const SensorJoy> SensorJoyConstPtr;
```

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"  

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;  

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();  
  
  // 默认机器人 IP 地址
  std::string robot_ip = "127.0.0.1";
  if (argc > 1)
  {
    // 如果提供了命令行参数，则使用命令行参数作为机器人 IP 地址
    robot_ip = argv[1];
  }
  
  // 初始化运动控制算法程序的通信运行环境
  if (!robot->init(robot_ip))
  {
    // 如果初始化失败，则退出程序
    exit(1);
  }
  
  // 订阅机器人遥控器数据
  robot->subscribeSensorJoy([&](const limxsdk::SensorJoyConstPtr &joy) {
    // L1 & R1 按下
    if (joy->buttons[4] == 1 && joy->buttons[7] == 1)
    {
      // 在这里执行相关操作
    }

    // 处理摇杆数据
    double axes_left_horizontal = joy->axes[0];
    double axes_left_vertical = joy->axes[1];
    double axes_right_horizontal = joy->axes[2];
    double axes_right_vertical = joy->axes[3];
  });
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  return 0;
}
```

### 4.1.8 subscribeDiagnosticValue 接口

| 函数名   | subscribeDiagnosticValue                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
| -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 函数原型 | void subscribeDiagnosticValue(std::function<void(const DiagnosticValueConstPtr&)> cb);                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| 功能概述 | 在真机部署中，该方法用于订阅机器人的诊断值和状态信息。当机器人发出诊断值时，系统会调用指定的回调函数，并传递包含诊断值的 DiagnosticValue 结构体常量指针给回调函数进行处理。这可以帮助实时监控机器人的健康状态，并及时做出反应以处理可能的问题。                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
| 参数     | cb: 用于接收机器人诊断值的回调函数，其参数类型为 DiagnosticValueConstPtr，即指向 DiagnosticValue 结构体常量的共享指针。DiagnosticValue 结构体包含了机器人诊断值的信息，包括时间戳、级别、名称、代码和消息字段。                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
| 返回值   | 无                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |

备注：DiagnosticValue 数据结构原型如下：

```cpp
/**
 * @struct DiagnosticValue
 *
 * @brief 结构体，表示诊断值。
 *
 * 此结构体包含有关诊断级别、名称、代码和消息的信息。
 */
struct DiagnosticValue {
  enum { OK = 0 };         // 正常状态的诊断级别
  enum { WARN = 1 };       // 警告状态的诊断级别
  enum { ERROR = 2 };      // 错误状态的诊断级别

  uint64_t stamp;          // 时间戳，单位为纳秒。
  int32_t level;           // 与诊断值相关联的级别。
  std::string name;        // 标识诊断值的名称。
  int32_t code;            // 与诊断值对应的代码。
  std::string message;     // 与诊断值相关的详细消息。
};

// DiagnosticValue 智能指针类型的定义
typedef std::shared_ptr<DiagnosticValue> DiagnosticValuePtr;
typedef std::shared_ptr<DiagnosticValue const> DiagnosticValueConstPtr;
```

代码示例：

```cpp
#include <thread>

// 包含 limxsdk::Humanoid 头文件，用于引入 Humanoid 类
#include "limxsdk/humanoid.h"  

// 使用 limxsdk 命名空间，简化对 Humanoid 类的引用
using namespace limxsdk;  

int main(int argc, char *argv[]){
  // 获取 Humanoid 类的单例实例
  Humanoid* robot = Humanoid::getInstance();  
  
  // 默认机器人 IP 地址
  std::string robot_ip = "127.0.0.1";
  if (argc > 1)
  {
    // 如果提供了命令行参数，则使用命令行参数作为机器人 IP 地址
    robot_ip = argv[1];
  }
  
  // 初始化运动控制算法程序的通信运行环境
  if (!robot->init(robot_ip))
  {
    // 如果初始化失败，则退出程序
    exit(1);
  }
  
  // 订阅机器人诊断数据
  robot->subscribeDiagnosticValue([&](const DiagnosticValueConstPtr& msg) {
    // 在这里处理机器人诊断值
    // 例如，可以根据诊断值的级别和消息来采取相应的措施
    std::cout << "Diagnostic Value: " << msg->name << std::endl;
    std::cout << "Level: " << msg->level << std::endl;
    std::cout << "Code: " << msg->code << std::endl;
    std::cout << "Message: " << msg->message << std::endl;
  });
  
  // 无限循环以保持程序运行
  while (true)
  {
    // 休眠 1000 毫秒
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  return 0;
}
```

### 4.1.9 publishJsonMessage 接口

| 函数名   | **publishJsonMessage**                                                                                                 |
| -------- | ------------------------------------------------------------------------------------------------------------------ |
| 函数原型 | void publishJsonMessage(const std::string &json_payload);                                                         |
| 功能概述 | 向机器人发送 "上层应用协议接口" 的 JSON 格式消息。                                                                |
| 参数     | json_payload: 符合 "上层应用协议接口" 协议的 JSON 字符串。 示例：{"accid": "xxx", "title": "request_xxx", "timestamp": xxx, "guid": "xxx", "data": {}} |
| 返回值   | 无                                                                                                                 |
| 备注     | **高阶开发模式下有效**                                                                                             |

**代码示例**

```cpp
#include <thread>

#include "limxsdk/humanoid.h"

using namespace limxsdk;

int main(int argc, char *argv[]) {
  Humanoid* robot = Humanoid::getInstance();
  
  std::string robot_ip = "10.192.1.2";
  if (argc > 1) {
    robot_ip = argv[1];
  }
  
  if (!robot->init(robot_ip)) {
    exit(1);
  }
  
  std::string json_payload = R"({
    "accid": "HU_D03_01",
    "title": "request_get_joint_state",
    "timestamp": 1672373633989,
    "guid": "746d937cd8094f6a98c9577aaf213d98",
    "data": {}
  })";
  
  robot->publishJsonMessage(json_payload);
  
  while (true) {
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  
  return 0;
}
```

### 4.1.10 subscribeJsonMessage 接口

| 函数名   | **subscribeJsonMessage**                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 函数原型 | void subscribeJsonMessage(std::function<void(const std::string &)> cb);                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
| 功能概述 | 注册一个回调函数，用于处理来自机器人的 "上层应用协议接口" 调用的响应和通知。 该回调函数会在以下两种场景中被调用： 1. 当机器人对之前发送的 JSON 命令（publishJsonMessage）返回响应时 2. 当机器人主动发起通知（未经请求的消息）时                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| 参数     | cb: 回调函数，原型为 void(const std::string &json_payload) 其中 json_payload 包含： - 命令响应：{"accid": "xxx", "title": "response_xxx", "timestamp": xxx, "guid": "xxx", "data": {}} - 通知：{"accid": "xxx", "title": "notify_xxx", "timestamp": xxx, "guid": "xxx", "data": {}}                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| 返回值   | 无                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| 备注     | **高阶开发模式下有效**                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |

**代码示例**：

```cpp
#include <thread>

#include "limxsdk/humanoid.h"

using namespace limxsdk;

int main(int argc, char *argv[]) {
  Humanoid* robot = Humanoid::getInstance();
  
  std::string robot_ip = "10.192.1.2";
  if (argc > 1) {
    robot_ip = argv[1];
  }
  
  if (!robot->init(robot_ip)) {
    exit(1);
  }
  
  robot->subscribeJsonMessage([&](const std::string & json_payload) {
    std::cout << json_payload << std::endl;
  });
  
  while (true) {
    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
  }
  
  return 0;
}
```

### 4.1.11 参考例程

Github: [https://github.com/limxdynamics/humanoid-rl-deploy-ros](https://github.com/limxdynamics/humanoid-rl-deploy-ros)

## 4.2 Python 运动控制开发接口

提供与 C++ 相同功能的 [Python 运动控制算法开发接口](https://github.com/limxdynamics/pointfoot-sdk-lowlevel/tree/master/python3)，**使得不熟悉 C++ 编程语言的开发者能够使用 Python 进行运动控制算法的开发。**

### 4.2.1 安装运动控制开发库

- **Linux x86_64 环境**

```bash
pip install python3/amd64/limxsdk-*-py3-none-any.whl
```

- **Linux aarch64 环境**

```bash
pip install python3/aarch64/limxsdk-*-py3-none-any.whl
```

- **Windows 环境**

```bash
pip install python3/win/limxsdk-*-py3-none-any.whl
```

### 4.2.2 __init__ 接口

| 函数名   | __init__                                         |
| -------- | ------------------------------------------------ |
| 函数原型 | def __init__(self, robot_type: robot.RobotType) |
| 功能概述 | 在初始化时，指定机器人的类型，并创建一个相应类型的本地机器人实例。 |
| 参数     | robot_type：表示机器人类型的枚举值，点足为RobotType.Humanoid。 |
| 返回值   | 无                                               |
| 备注     | 无                                               |

**代码示例**：

```python
import sys
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType

if __name__ == '__main__':
  # 创建一个类型为Humanoid的Robot实例
  robot = Robot(RobotType.Humanoid)
```

### 4.2.3 init 接口

| 函数名   | init                                        |
| -------- | ------------------------------------------- |
| 函数原型 | def init(self, robot_ip: str = "127.0.0.1") |
| 功能概述 | 初始化运动控制算法程序的通信运行环境，通常在主函数中调用其它接口之前调用，完成初始化工作。 |
| 参数     | robot_ip：机器人的 IP 地址。对于仿真，通常设置为 "127.0.0.1"，而对于真实机器人，可能设置为 "10.192.1.2"。 |
| 返回值   | 成功：返回True<br>失败：返回False            |
| 备注     | 无                                          |

**代码示例**：

```python
import sys
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType

if __name__ == '__main__':
  # 创建一个类型为Humanoid的Robot实例
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "127.0.0.1"
  # 检查是否提供了命令行参数作为机器人IP
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用IP地址初始化机器人的通信运行环境
  if not robot.init(robot_ip):
    sys.exit()
```

### 4.2.4 getMotorNumber 接口

| 函数名   | getMotorNumber                                   |
| -------- | ------------------------------------------------ |
| 函数原型 | def getMotorNumber(self)                         |
| 功能概述 | 获取机器人中的电机数量。                         |
| 参数     | 无                                               |
| 返回值   | 返回一个无符号整数，表示机器人中的总电机数量。   |
| 备注     | 通常情况下，点足机器人的电机数量为6个            |

**代码示例**：

```python
import sys
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType

if __name__ == '__main__':
  # 创建一个 Humanoid 类型的 Robot 实例
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "127.0.0.1"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 获取机器人中的电机数量
  motor_number = robot.getMotorNumber()
```

### 4.2.5  subscribeImuData 接口

| 函数名   | subscribeImuData                                                 |
| -------- | ---------------------------------------------------------------- |
| 函数原型 | def subscribeImuData(self, callback: Callable[[datatypes.ImuData], Any]) |
| 功能概述 | 订阅机器人的 IMU数据，并在接收到新的 IMU 数据时调用指定的回调函数。 |
| 参数     | callback：用于处理新 IMU 数据的回调函数。                        |
| 返回值   | 成功：返回True<br>失败：返回False                                |

**备注**：datatypes.ImuData 数据结构原型如下：

```python
import sys

class ImuData(object):
  __slots__ = ['stamp','acc','gyro','quat']
  def __init__(self):
    self.stamp = 0 # 时间戳，通常表示记录或生成这些数据的时间，以纳秒为单位
    self.acc = [0. for x in range(0, 3)]  # 用于存储 IMU（惯性测量单元）加速度计数据，用于跟踪三个轴上的线性加速度
    self.gyro = [0. for x in range(0, 3)] # 用于存储 IMU 陀螺仪数据，用于跟踪角速度或旋转速度
    self.quat = [0. for x in range(0, 4)] # 用于存储 IMU 四元数数据，表示在三维空间中的方向
```

**代码示例**：

```python
import sys
from functools import partial
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType
import limxsdk.datatypes as datatypes

class RobotReceiver:
  # 订阅机器人的 IMU数据
  def imuDataCallback(self, imu: datatypes.ImuData):
    print("\n------\nrobot_state:" + \
          "\n  stamp: " + str(imu.stamp) + \
          "\n  acc: " + str(imu.acc) + \
          "\n  gyro: " + str(imu.gyro) + \
          "\n  quat: " + str(imu.quat))

if __name__ == '__main__':
  # 创建一个 Robot 实例，类型为 Humanoid
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "127.0.0.1"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 创建一个 RobotReceiver 实例来处理回调
  receiver = RobotReceiver()
  
  # 创建回调函数的 partial 函数
  imuDataCallback = partial(receiver.imuDataCallback)
  
  # 订阅机器人IMU数据
  robot.subscribeImuData(imuDataCallback)
```

### 4.2.6  subscribeRobotState 接口

| 函数名   | subscribeRobotState                                              |
| -------- | ---------------------------------------------------------------- |
| 函数原型 | def subscribeRobotState(self, callback: Callable[[datatypes.RobotState], Any]) |
| 功能概述 | 订阅接收关于机器人状态的更新。                                   |
| 参数     | callback：回调函数，当接收到机器人状态更新时将被调用。回调函数参数指向datatypes.RobotState 对象。<br>- datatypes.RobotState数据结构字段：<br>  - stamp：时间戳，通常表示记录或生成这些数据的时间。<br>  - tau：用于存储当前估计的输出扭矩（以牛顿米为单位）的向量。<br>  - q：用于存储当前角度（以弧度为单位）的向量。<br>  - dq：用于存储当前速度（以弧度每秒为单位）的向量。<br>  - motor_names：用于存储对应的关节名称。 |
| 返回值   | 成功：返回True<br>失败：返回False                                |

**备注**：datatypes.RobotState 数据结构原型如下：

```python
import sys

class RobotState(object):
  __slots__ = ['stamp','tau','q','dq']
  def __init__(self):
    self.stamp = 0 # 时间戳，通常表示记录或生成这些数据的时间，以纳秒为单位
    self.tau = []  # 用于存储当前估计的输出扭矩（以牛顿米为单位）的向量
    self.q = []    # 用于存储当前角度（以弧度为单位）的向量
    self.dq = []   # 用于存储当前速度（以弧度每秒为单位）的向量
    self.motor_names = []   # 用于存储对应的关节名称。
```

**代码示例**：

```python
import sys
from functools import partial
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType
import limxsdk.datatypes as datatypes

class RobotReceiver:
  # 用于接收机器人状态的回调函数
  def robotStateCallback(self, robot_state: datatypes.RobotState):
    print("
------
robot_state:" + \
          "
  stamp: " + str(robot_state.stamp) + \
          "
  tau: " + str(robot_state.tau) + \
          "
  q: " + str(robot_state.q) + \
          "
  dq: " + str(robot_state.dq))

if __name__ == '__main__':
  # 创建一个 Robot 实例，类型为 Humanoid
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "127.0.0.1"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 创建一个 RobotReceiver 实例来处理回调
  receiver = RobotReceiver()
  
  # 创建回调函数的 partial 函数
  robotStateCallback = partial(receiver.robotStateCallback)
  
  # 订阅机器人状态
  robot.subscribeRobotState(robotStateCallback)
```

### 4.2.7  publishRobotCmd 接口

| 函数名   | publishRobotCmd                                              |
| -------- | ------------------------------------------------------------ |
| 函数原型 | def publishRobotCmd (self, cmd: datatypes.RobotCmd)         |
| 功能概述 | 发布一个命令来控制机器人的动作。                             |
| 参数     | cmd：表示所需机器人命令的 datatypes.RobotCmd 对象，包含以下字段：<br>  - stamp：记录或生成数据时的时间戳，以纳秒为单位。<br>  - q：存储所需的关节角度（以弧度为单位）的向量。<br>  - dq：存储所需的关节速度（以弧度每秒为单位）的向量。<br>  - tau：存储所需的输出扭矩（以牛顿米为单位）的向量。<br>  - Kp：存储所需的位置刚度（以牛顿米每弧度为单位）的向量。<br>  - Kd：存储所需的速度刚度（以牛顿米每弧度每秒为单位）的向量。<br>  - motor_names：存储需要控制的关节名称。 |
| 参数取值 | - q、dq、tau：在urdf中已定义范围，举例如下：<br>  - joint的<limit>字段中描述了每个关节的q、dq、tau取值范围：<br>    - lower和upper共同对应"q"，表示控制位置范围（单位为弧度）；<br>    - effort对应"tau"，表示扭矩峰值（单位为牛顿米）；<br>    - velocity对应"dq"，表示速度峰值（单位为弧度每秒）；<br>- Kp、Kd可用值（用户自行开发控制器时需根据实际效果调整取值）： |
| 返回值   | 成功：返回True<br>失败：返回False                            |

**备注**：datatypes.RobotCmd 数据结构原型如下：

```python
import sys

class RobotCmd(object):
  __slots__ = ['stamp','mode','q','dq','tau','Kp','Kd']
  def __init__(self):
    self.stamp = 0 # 时间戳（以纳秒为单位），表示记录或生成数据时的时间。
    self.mode = [] # 机器人的期望工作模式。
    self.q = []    # 存储期望角度的向量（以弧度为单位）
    self.dq = []   # 存储期望速度的向量（以弧度每秒为单位）。
    self.tau = []  # 存储期望输出扭矩的向量（以牛顿米为单位）。
    self.Kp = []   # 存储期望位置刚度的向量（以牛顿米每弧度为单位）。
    self.Kd = []   # 存储期望速度刚度的向量（以牛顿米每弧度每秒为单位）。
    self.motor_names = []   # 存储需要控制的关节名称。
```

**代码示例**：

```python
import sys
import time
import limxsdk.robot.Rate as Rate
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType
import limxsdk.datatypes as datatypes

if __name__ == '__main__':
  # 创建一个 Robot 实例，类型为 Humanoid
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "127.0.0.1"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 获取关节偏移、关节限制和电机数量信息
  joint_offset = robot.getJointOffset()
  joint_limit = robot.getJointLimit()
  motor_number = robot.getMotorNumber()
  
  # 主循环以连续发布机器人命令
  rate = Rate(500) # 1500 Hz
  cmd_msg = datatypes.RobotCmd()
  while True:
    # 设置时间戳、控制模式、关节位置、速度、力矩、Kp 和 Kd 的默认值
    cmd_msg.stamp = time.time_ns()
    cmd_msg.mode = [1.0 for _ in range(motor_number)]
    cmd_msg.q = [1.0 for _ in range(motor_number)]
    cmd_msg.dq = [1.0 for _ in range(motor_number)]
    cmd_msg.tau = [1.0 for _ in range(motor_number)]
    cmd_msg.Kp = [1.0 for _ in range(motor_number)]
    cmd_msg.Kd = [1.0 for _ in range(motor_number)]
    robot.publishRobotCmd(cmd_msg)  # 发布机器人命令
    rate.sleep()  # 控制循环频率
```

### 4.2.8  subscribeSensorJoy 接口

| 函数名   | subscribeSensorJoy                                           |
| -------- | ------------------------------------------------------------ |
| 函数原型 | def subscribeSensorJoy(self, callback: Callable[[datatypes.SensorJoy], Any]) |
| 功能概述 | 在真机部署中，该方法用于订阅来自机器人遥控器的数据。当机器人接收到遥控器的数据时，将会调用指定的回调函数，并传递包含遥控器数据的 datatypes.SensorJoy 结构体常量指针给回调函数进行处理。 |
| 参数     | callback: 表示回调函数，用于接收机器人遥控器的数据。回调函数的参数类型为 datatypes.SensorJoy |
| 返回值   | 成功：返回True<br>失败：返回False                            |

**备注**: datatypes.SensorJoy 数据结构原型如下：

```python
import sys

class SensorJoy(object):
  __slots__ = ['stamp','axes','buttons']
  def __init__(self):
    self.stamp = 0     # 与传感器输入相关的时间戳，单位为纳秒。
    self.axes = []     # 表示操纵摇杆的值。
    self.buttons = []  # 表示操纵按钮状态的值。
```

**代码示例**：

```python
import sys
import time
from functools import partial
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType
import limxsdk.datatypes as datatypes

class RobotReceiver:
  # 用于接收遥控器数据的回调函数
  def sensorJoyCallback(self, sensor_joy: datatypes.SensorJoy):
    print("
------
sensor_joy:" + \
          "
  stamp: " + str(sensor_joy.stamp) + \
          "
  axes: " + str(sensor_joy.axes) + \
          "
  buttons: " + str(sensor_joy.buttons))

if __name__ == '__main__':
  # 创建一个 Robot 实例，类型为 Humanoid
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "127.0.0.1"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 创建一个 RobotReceiver 实例来处理回调
  receiver = RobotReceiver()
  
  # 创建回调函数的 partial 函数
  sensorJoyCallback = partial(receiver.sensorJoyCallback)
  
  # 订阅机器人遥控数据
  robot.subscribeSensorJoy(sensorJoyCallback)
```

### 4.2.9  subscribeDiagnosticValue 接口

| 函数名   | subscribeDiagnosticValue                                     |
| -------- | ------------------------------------------------------------ |
| 函数原型 | def subscribeDiagnosticValue(self, callback: Callable[[datatypes.DiagnosticValue], Any]) |
| 功能概述 | 在真机部署中，该方法用于订阅机器人的诊断值和状态信息。当机器人发出诊断值时，系统会调用指定的回调函数，并传递包含诊断值的 datatypes.DiagnosticValue 结构对象给回调函数进行处理。这可以帮助实时监控机器人的健康状态，并及时做出反应以处理可能的问题。 |
| 参数     | callback: 用于接收机器人诊断值的回调函数，其参数类型为 datatypes.DiagnosticValue。datatypes.DiagnosticValue 结构体包含了机器人诊断值的信息，包括时间戳、级别、名称、代码和消息字段。 |
| 返回值   | 成功：返回True<br>失败：返回False                            |

**备注**: datatypes.DiagnosticValue 数据结构原型如下：

```python
import sys

class DiagnosticValue(object):
  __slots__ = ['stamp','level','name','code','message']
  def __init__(self):
    self.stamp = 0 # 时间戳，单位为纳秒。
    self.level = 0 # 与诊断值相关联的级别 - 0: OK, 1: WARN, 2: ERROR
    self.name = '' # 标识诊断值的名称。
    self.code = 0  # 与诊断值对应的代码。
    self.message = ''  # 与诊断值相关的详细消息。
```

**代码示例**：

```python
import sys
from functools import partial
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType
import limxsdk.datatypes as datatypes

class RobotReceiver:
  # 用于接收诊断值的回调函数
  def diagnosticValueCallback(self, diagnostic_value: datatypes.DiagnosticValue):
    print("
------
diagnostic_value:" + \
          "
  stamp: " + str(diagnostic_value.stamp) + \
          "
  name: " + diagnostic_value.name + \
          "
  level: " + str(diagnostic_value.level) + \
          "
  code: " + str(diagnostic_value.code) + \
          "
  message: " + diagnostic_value.message)

if __name__ == '__main__':
  # 创建一个 Robot 实例，类型为 Humanoid
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "127.0.0.1"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 创建一个 RobotReceiver 实例来处理回调
  receiver = RobotReceiver()
  
  # 创建回调函数的 partial 函数
  diagnosticValueCallback = partial(receiver.diagnosticValueCallback)
  
  # 订阅机器人诊断信息
  robot.subscribeDiagnosticValue(diagnosticValueCallback)
```

### 4.2.10  publishJsonMessage 接口

| 函数名   | publishJsonMessage                                           |
| -------- | ------------------------------------------------------------ |
| 函数原型 | def publishJsonMessage(self, json_payload: str)             |
| 功能概述 | 向机器人发送 "上层应用协议接口" 的 JSON 格式消息。           |
| 参数     | json_payload: 符合 "上层应用协议接口" 协议的 JSON 字符串。<br>示例：{"accid": "xxx", "title": "request_xxx", "timestamp": xxx, "guid": "xxx", "data": {}} |
| 返回值   | 无                                                           |
| 备注     | 高阶开发模式下有效                                           |

**代码示例**：

```python
import sys
import time
import limxsdk.robot.Rate as Rate
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType
import limxsdk.datatypes as datatypes

if __name__ == '__main__':
  # 创建一个 Robot 实例，类型为 Humanoid
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "10.192.1.2"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 设置要发送的协议内容
  json_payload = '''{
    "accid": "HU_D03_01", # 替换为真实机器人SN
    "title": "request_get_joint_state",
    "timestamp": 1672373633989,
    "guid": "746d937cd8094f6a98c9577aaf213d98",
    "data": {}
  }'''
  
  # 发送JSON协议
  robot.publishJsonMessage(json_payload)
  
  # 保持程序运行
  try:
    while True:
      time.sleep(1)
  except KeyboardInterrupt:
    print("程序被用户中断")
```

### 4.2.11  subscribeJsonMessage 接口

| 函数名   | subscribeJsonMessage                                         |
| -------- | ------------------------------------------------------------ |
| 函数原型 | def subscribeJsonMessage(self, callback: Callable[[str], Any]) |
| 功能概述 | 注册一个回调函数，用于处理来自机器人的 "上层应用协议接口" 调用的响应和通知。<br>该回调函数会在以下两种场景中被调用：<br>1. 当机器人对之前发送的 JSON 命令（publishJsonMessage）返回响应时<br>2. 当机器人主动发起通知（未经请求的消息）时 |
| 参数     | callback: 回调函数, 其中 json_payload 包含：<br>- 命令响应：{"accid": "xxx", "title": "response_xxx", "timestamp": xxx, "guid": "xxx", "data": {}}<br>- 通知：{"accid": "xxx", "title": "notify_xxx", "timestamp": xxx, "guid": "xxx", "data": {}} |
| 返回值   | 无                                                           |
| 备注     | 高阶开发模式下有效                                           |

**代码示例**：

```python
import sys
import time
from functools import partial
import limxsdk.robot.Robot as Robot
import limxsdk.robot.RobotType as RobotType
import limxsdk.datatypes as datatypes

class RobotReceiver:
  # 处理来自机器人的 "上层应用协议接口" 调用的响应和通知
  def jsonMessageCallback(self, json_payload: str):
    print("
------
json_payload:" + json_payload)

if __name__ == '__main__':
  # 创建一个 Robot 实例，类型为 Humanoid
  robot = Robot(RobotType.Humanoid)
  
  robot_ip = "10.192.1.2"
  # 检查是否提供了机器人 IP 的命令行参数
  if len(sys.argv) > 1:
    robot_ip = sys.argv[1]
  
  # 使用 robot_ip 初始化机器人
  if not robot.init(robot_ip):
    sys.exit()
  
  # 创建一个 RobotReceiver 实例来处理回调
  receiver = RobotReceiver()
  
  # 创建回调函数的 partial 函数
  jsonMessageCallback = partial(receiver.jsonMessageCallback)
  
  # 订阅机器人遥控数据
  robot.subscribeJsonMessage(jsonMessageCallback)
```

### 4.2.12 参考例程

Github: https://github.com/limxdynamics/humanoid-rl-deploy-python



# 5 查看/设置机器人型号

在编译和运行RL训练、控制算法及仿真器程序时，选择正确的机器人型号至关重要。通过查看机器人型号并将其设置到环境变量 `ROBOT_TYPE` 中，确保在不同任务中准确识别并应用相应的机器人模型。



**查看和配置机器人型号步骤：**

1. 选择并连接您机器人Wi-Fi 热点，密码为：`12345678`

![图片](data:image/webp;base64,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)

1. 在浏览器中输入`http://10.192.1.2:8080`进入“机器人信息页”，查看机器人信息。如下图所示，页面中显示的SN (序列号) 为HU_D03_03_001，其中HU_D03_03为机器人型号。

![图片](data:image/webp;base64,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)

1. 设置机器人型号：打开 Bash 终端，输入以下 Shell 命令来设置机器人型号。这样在二次开发时，您将能获取到正确的机器人型号信息。

```bash
echo 'export ROBOT_TYPE=HU_D03_03' >> ~/.bashrc && source ~/.bashrc
```

# 6 机器人仿真器

MuJoCo 是一款轻量级且高性能的物理仿真器，专为多关节机器人和机械系统设计。它具备高效的物理引擎，能够精确处理接触和摩擦，且无需依赖 ROS，可独立运行。凭借其高速计算能力，MuJoCo 被广泛应用于机器人仿真和强化学习，尤其适合对仿真效率要求较高的场景。

## 6.1 运行仿真器步骤

1. 运行环境：推荐 Pyhon 3.8 及以上版本

2. 打开一个 Bash 终端。

3. 下载 MuJoCo 仿真器代码：

```bash
git clone --recurse git@github.com:limxdynamics/humanoid-mujoco-sim.git
```

4. 安装运动控制开发库：

- Linux x86_64 环境

```bash
pip install humanoid-mujoco-sim/limxsdk-lowlevel/python3/amd64/limxsdk-*-py3-none-any.whl
```

- Linux aarch64 环境

```bash
pip install humanoid-mujoco-sim/limxsdk-lowlevel/python3/aarch64/limxsdk-*-py3-none-any.whl
```

1. 设置机器人型号：请参考"查看/设置机器人型号"章节，查看您的机器人型号。如果尚未设置，请按照以下步骤进行设置。

- 通过 Shell 命令 `tree -L 3 -P "meshes" -I "urdf|world|xml|usd" humanoid-mujoco-sim/humanoid-description` 列出可用的机器人类型：

```bash
limx@limx:~$ tree -L 3 -P "meshes" -I "urdf|world|xml|usd" humanoid-mujoco-sim/humanoid-description
humanoid-mujoco-sim/humanoid-description
├── HU_D03_description
│   └── meshes
│       └── HU_D03_03
└── HU_D04_description
    └── meshes
        └── HU_D04_01
```

- 以`HU_D04_01`（请根据实际机器人类型进行替换）为例，设置机器人型号类型：

```bash
echo 'export ROBOT_TYPE=HU_D04_01' >> ~/.bashrc && source ~/.bashrc
```

1. 运行 MuJoCo 仿真器：

```bash
python humanoid-mujoco-sim/simulator.py
```

## 6.2 演示效果(请以实际为准)
![图片](data:image/webp;base64,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)



# 7 RL 算法部署

## 7.1 基于标准C++进行部署
Github项目地址：https://github.com/limxdynamics/humanoid-rl-deploy-cpp，它是一个在标准C++中实现的轻量级算法框架。无需 ROS1/ROS2 即可快速部署训练的模型。

## 7.2 基于Python进行部署
Github项目地址：https://github.com/limxdynamics/humanoid-rl-deploy-python，它是一种基于Python的强化学习部署算法框架，它简化了在Oli机器人上部署训练模型的过程。

## 7.3 基于ROS2 进行部署
Github项目地址：https://github.com/limxdynamics/humanoid-rl-deploy-ros2，它是基于 [ROS2](https://www.ros.org) 的强化学习部署框架，可在 Oli 机器人上快速部署经过训练的模型。

## 7.4 基于ROS1 进行部署
Github项目地址：https://github.com/limxdynamics/humanoid-rl-deploy-ros，它是基于[ROS1](https://www.ros.org)的强化学习部署框架，可以在Oli机器人上快速部署经过训练的模型。



# 8 日志和数据包

- **机器人系统自动录制数据：** IMU数据(ImuData)、状态数据（/joint/state）、控制数据（/joint/cmd）、运行日志数据等重要数据，这些数据对于机器人的运动控制分析至关重要。

- **访问并下载机器人数据：** 机器人将会记录运行时的日志数据，以便在需要时进行故障排查和性能优化，电脑与机器人 WiFi 热点连接后浏览器输入 `http://10.192.1.2:8090`，可自行选择下载所需数据。

## 8.1 数据包可视化分析方法

- **数据包下载：** 下载 `.bag` 文件后，可以使用PlotJuggler可视化工具加载这些数据包进行分析。需要特别注意的是，如果下载的是 `.bag.active` 文件，需要使用如下Shell命令把它重新索引 `.bag.active` 文件，生成一个新的 `.bag` 文件，以便PlotJuggler加载。

```bash
rosbag reindex your_file.bag.active
mv your_file.bag.active your_file.bag
```

- **可视化查看：** 通过Shell命令 `rosrun plotjuggler plotjuggler -n` 启动PlotJuggler可视化工具。如下图所示加载数据包进行可视化分析。

## 8.2 日志及诊断埋点数据

如下图所示分别为日志和埋点结构化数据。在需要时可以用于故障排查和性能优化。

![图片](data:image/png;base64,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)


# 9 机器人软件升级

 软件升级注意事项：

1. 请确保设备电量不低于 30%。升级过程中如发生断电，可能导致设备无法正常使用
2. 请提前将机器人切换至零力矩模式或阻尼模式。升级完成后设备将自动重启，若机器人处于站立状态,可能存在跌倒风险。

通过浏览器进入机器人管理页面,选择本地提前下载好的机器人软件版本进行升级。具体步骤如下：

1. 连接 Wi-Fi：
   - 选择并连接机器人的 Wi-Fi 热点，密码为：12345678

   ![图片](data:image/png;base64,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)

2. 访问管理页面：
   - 在浏览器地址栏输入： `http://10.192.1.2:8080` 进入机器人管理页面。

3. 选择并升级软件：
   - 依次选择"版本管理 -> 浏览 -> 升级"。
   - 升级完成后，机器人主控电脑将自动重启。

   ![图片](data:image/png;base64,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)



# 10 开发者电脑

开发者电脑主要用于开发机器人相关算法及应用程序。可以通过 WiFi 连接机器人本体系统登录到开发者电脑，具体步骤如下：

1. 连接Wi-Fi：
   - 选择并连接机器人的 Wi-Fi 热点，密码为：12345678

   ![图片](data:image/png;base64,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)

2. 通过 SSH 登录开发者电脑系统：
   - 登录地址：10.192.1.3
   - 登录密码：123456
   - 在终端中输入以下命令（首次连接需确认指纹）：

```bash
ssh guest@10.192.1.3
```

- 开发者电脑系统配置：
  - 操作系统：Ubuntu 22.04 （Jetpack 6.2.1）
  - ROS2：系统默认安装ROS2 Humble 版本机器人系统
  - ROS1：系统默认安装ROS1 Noetic 版本机器人系统Docker，进入方法如下：

```bash
sudo docker exec -it ros_noetic /bin/bash
```

# 11 Realsense 相机数据获取

**注意事项：**

1. 机器人开机后默认会自动启动相机驱动。因此，在进行以下操作前，请先关闭相机驱动的自动启动功能。关闭方法请参考下文说明。该功能仅支持主控版本 V2.0.33 及以上。
2. 关闭相机驱动自动启动功能后，我司配套的数据采集套件（数采套件）将无法正常使用。请根据实际需求决定是否执行该操作。

## 11.1 关闭相机驱动自启动

1. 在浏览器地址栏输入 `http://10.192.1.2:8080`，进入以下界面。

   ![进入机器人管理页面](data:image/png;base64,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)

2. 设置关闭并保存。

   ![关闭相机驱动自动启动并保存](data:image/png;base64,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)

## 11.2 获取相机数据

1. 登录开发者电脑：
   - 请按照“开发者电脑”章节中的步骤登录该电脑。

2. 启动 Realsense 的 ROS 节点以获取相机数据：
   - 启动方式参考链接：[realsense-ros](https://github.com/IntelRealSense/realsense-ros)
   - 电脑已预装 Realsense 相机的 SDK：
     - 版本为 v2.56.3，官方下载链接：[librealsense v2.56.3](https://github.com/IntelRealSense/librealsense/releases/tag/v2.56.3)，可基于此官方 SDK 自主开发应用程序来获取数据。

3. 示例代码说明：
   - 相机命名规则：
     - 默认命名：脚本会将多个相机的 topic 前缀命名为 `camera` 加上序号（如 `camera0`、`camera1`）。
     - 自定义命名：可通过修改脚本，根据相机的序列号（Serial Number）指定 topic 前缀，而非使用默认的 `camera + counter` 命名规则。

以下代码示例展示了如何获取多个相机的数据：

1. 通过 SSH 登录开发者电脑系统
2. 登录 ROS1 系统

```bash
sudo docker exec -it ros_noetic /bin/bash
```

3. 将下面的脚本保存为 `rs_camera.sh`：

```bash
#!/bin/bash

source /opt/ros/noetic/setup.bash

# Function to detect connected RealSense cameras
detect_cameras() {
    # List all connected RealSense cameras, excluding Asic Serial Number
    serial_numbers=($(rs-enumerate-devices | grep "Serial Number" | grep -v "Asic" | awk '{print $NF}'))
    echo "${serial_numbers[@]}"
}

# Loop to check for the launch flag file and connected cameras
while true; do
    serial_numbers=($(detect_cameras))

    # Check if any cameras were found
    if [ ${#serial_numbers[@]} -gt 0 ]; then
        echo "Detected ${#serial_numbers[@]} cameras."
        break  # Exit the loop if cameras are detected
    else
        echo "No RealSense cameras detected. Retrying in 5 seconds..."
        sleep 5  # Wait for a while before retrying
    fi
done

# Automatically start a ROS node for each detected camera
if [ ${#serial_numbers[@]} -gt 0 ]; then
    for i in "${!serial_numbers[@]}"; do
        serial=${serial_numbers[$i]}

        # Default camera naming using index (camera0, camera1, ...)
        # Customize camera naming by modifying the code below
        camera_topic="camera$i"

        # Example: Custom camera naming based on serial number
        # Uncomment and replace with your actual serial numbers
        # if [[ "$serial" == "0123456789" ]]; then
        #     camera_topic="head"  # Name specific camera as "head"
        # elif [[ "$serial" == "9876543210" ]]; then
        #     camera_topic="chest" # Name another camera as "chest"
        # fi

        echo "Starting ROS node for camera $serial (topic prefix: $camera_topic)..."
        roslaunch realsense2_camera rs_camera.launch \
            serial_no:=$serial \
            camera:=$camera_topic \
            enable_pointcloud:=True \
            enable_accel:=True \
            enable_gyro:=True \
            enable_sync:=True \
            unite_imu_method:=linear_interpolation &
        sleep 10  # Optional: wait a bit before starting the next camera
    done

    # Wait for all background processes to finish
    wait
else
    echo "No cameras to start."
fi
```

4. 在终端执行脚本，启动相机节点：

```bash
/bin/bash rs_camera.sh
```

5. 在另一个终端中，通过 `rostopic list` 验证结果：

```bash
rostopic list
```
