# Luna SDK Development Guide

| **Version** | **Date** | **Description of Changes** | **Remarks** |
| --- | --- | --- | --- |
| V1.0 | 2026-08-26 | Initial Release |  |
| V1.1 | 2026-10-19 | Added Whole-Body Teleoperation (WBT) protocol interfaces |  |

# 1. SDK Introduction

## 1.1 High-Level Application Protocol Interface

### 1.1.1 Overview

The robot receives user request commands through the WebSocket communication port `5000`, such as making the robot stand up, squat down, walk, etc. WebSocket is a real-time communication protocol that establishes a persistent connection between the robot and the user端 for fast and efficient transmission of control information and data.

### 1.1.2 Communication Protocol Format

When the robot receives commands from the client via WebSocket, data is transmitted using the JSON communication protocol. This approach offers significant advantages: WebSocket is a full-duplex communication protocol that establishes a real-time, low-latency connection between the client and server, particularly suitable for frequently interacting application scenarios. The JSON data protocol, with its concise and highly readable structure, ensures intuitive and clear data transmission, with cross-platform and cross-language compatibility. The combination of WebSocket and JSON is not only programming language-agnostic and applicable to various devices and systems, but also improves development flexibility and maintenance convenience.

- The request data format contains the following fields:

  - `accid`: The robot's unique serial number, identifying its unique identity;
  - `title`: The command name, prefixed with "`request_`";
  - `timestamp`: The timestamp when the command is sent, in milliseconds;
  - `guid`: A unique command identifier used to distinguish different request commands. For synchronous interfaces, the `guid` value must be returned to the client in the "response_xxx" response message. After receiving the response message, the client can determine whether the command has been executed by comparing whether the `guid` value matches the value in the request command;
  - `data`: Contains the content of the request. Depending on specific requirements, it may include multiple sub-fields to store the data required by the request command, such as parameters for executing actions, text content for sending messages, etc.;
  - Example:

  ```Plain
  {
    "accid": "HU_L04_01_001", # Robot's unique serial number, identifying its unique identity
    "title": "request_xxx",   # Command name, prefixed with "request_"
    "timestamp": 1672373633989, # Timestamp when the command is sent, in milliseconds
    "guid": "746d937cd8094f6a98c9577aaf213d98", # Unique command identifier, used to distinguish different request commands
    "data": {}  # Contains the content of the request command
  }
  ```
- The response data format contains the following fields:

  - `accid`: The robot's unique serial number, identifying its unique identity;
  - `title`: The command name, prefixed with "`response_`";
  - `timestamp`: The timestamp when the command is sent, in milliseconds;
  - `guid`: Same as the `guid` value of the corresponding request command;
  - `data`: Should contain at least one "result" sub-field, used to store the execution result data of the request command. If needed, it may also include other sub-fields, such as error codes, error messages, and other information describing the operation result;
  - Example:

  ```JSON
  {
    "accid": "HU_L04_01_001",   # Robot's unique serial number, identifying its unique identity
    "title": "response_xxx",  # Command name, prefixed with "response_"
    "timestamp": 1672373633989, # Timestamp when the command is sent, in milliseconds
    "guid": "746d937cd8094f6a98c9577aaf213d98", # Same as the guid value of the corresponding request command
    "data": { # Contains the specific data content of the response command
      "result": "success"  # "result" stores whether the request command was processed successfully, its value is: "success or fail_xxx"
    }
  }
  ```
- Message Push: This is the process by which the robot proactively sends information to the client. This information can include the robot's serial number, current running status, executed operations, and other data. By promptly sending this information to the client, the robot can help the client better understand its working status, thereby better utilizing the services it provides. Its data format contains the following fields:

  - `accid`: The robot's unique serial number, identifying its unique identity;
  - `title`: The command name, prefixed with "`notify_`";
  - `timestamp`: The timestamp when the message is sent, in milliseconds;
  - `guid`: The guid value of the message, uniquely identifying this message;
  - `data`: Contains the message data content. Depending on specific requirements, it may include multiple sub-fields to store the data required by the request command;
  - Example:

  ```JSON
  {
    "accid": "HU_L04_01_001",   # Robot's unique serial number, identifying its unique identity
    "title": "notify_xxx",  # Message name, prefixed with "notify_"
    "timestamp": 1672373633989, # Timestamp when the message is sent, in milliseconds
    "guid": "746d937cd8094f6a98c9577aaf213d98", # The guid value of the message, uniquely identifying this message
    "data": { } # Contains the message data content
  }
  ```

### 1.1.3 Communication Testing Method

Postman is a popular API development environment that can be used to test WebSocket interfaces. To test WebSocket interfaces using Postman, follow these steps:

- Install Postman, download address: [https://www.postman.com/downloads/?utm_source=postman-home;](https://www.postman.com/downloads/?utm_source=postman-home;)
- Open Postman and create a WebSocket request;
- Connect to the robot's wireless network

  - After the robot is powered on, use your personal computer to connect to the robot's Wi-Fi, the name format is usually "HU_L04_xxx"
  - Enter the Wi-Fi password: `12345678`
- Enter the WebSocket interface address in the request URL, for example, "ws://10.192.1.2:5000";
- In "Message", enter the command request to be sent;
- Click the "Send" button to send the request command;
- After sending the command, you can receive the response message from the server. Use Postman's response window to view the data returned by the server and check whether it meets the expected result.

  ![图片展示的是Luna SDK开发指南中通信测试方法中使用Postman进行WebSocket请求的界面。界面上方显示“ws://10.192.1.2:5000 - My Workspace”，下方有多个WebSocket连接记录，如“ws://10.192.1.2:5000”等。中间区域有“Message”“Params”“Headers”“Settings”等输入框，下方“Response”区域显示了返回的JSON数据，如“{“accid”:“PF_TRONSA_042”,“title”:“notify_robot_info”}”等。该图与文档中使用Postman发送WebSocket请求并查看响应数据的内容相关。](data:image/jpeg;base64,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)

## 1.2 Basic Function Protocol Interfaces

### 1.2.1 Set Audio Prompt Language

#### 1.2.1.1 Request: request_set_audio_prompts_language

This protocol is used to set the robot's audio prompt language. After a successful request, the robot's subsequent voice prompts will use the specified language, and a switching confirmation prompt will be played to help the user confirm that the setting has taken effect. Request parameter, language values:

| language | Meaning | User Perception |
|-|-|-|
| cn | Chinese audio prompt | Subsequent prompts use Chinese, and a Chinese switching confirmation prompt is played |
| en | English audio prompt | Subsequent prompts use English, and an English switching confirmation prompt is played |

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_set_audio_prompts_language",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "language": "cn"
  }
}
```

#### 1.2.1.2 Response: response_set_audio_prompts_language

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_set_audio_prompts_language",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "success"
  }
}
```

##### result Values

| result | Meaning | User Prompt Suggestion |
|-|-|-|
| success | Setting successful | Audio prompt language has been switched |
| fail_no_language | Target language not provided | Please select an audio prompt language |
| fail_invalid_language | Language value not supported | Currently only Chinese and English are supported |
| fail_write_robot_info | Failed to save setting | Setting failed, please try again later |
| fail_play_audio_prompt_service_not_ready | Audio function not ready | Audio function not ready, please try again later |
| fail_play_audio_prompt_call | Switching confirmation prompt request failed | Switching confirmation failed, please retry |
| fail_play_audio_prompt | Switching confirmation prompt playback failed | Confirmation prompt not heard, please retry |

#### 1.2.1.3 Message Push: none

### 1.2.2 Connect to Wi-Fi Hotspot

#### 1.2.2.1 Request: request_connect_wifi

This protocol is used to send a request to the robot router, instructing the router to connect to a Wi-Fi hotspot with the specified SSID and return the connection result.

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_connect_wifi",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": { 
      "wifi_band": 0,  # Wi-Fi band: 0=5GHz, 1=2.4GHz
      "wifi_ssid": "Limx-Guests",  # Target Wi-Fi SSID (Wi-Fi name), case-sensitive, must match the actual hotspot
      "wifi_password": "LimX2024",  # Target Wi-Fi password, password for WPA2-PSK encrypted network
      "router_admin_password": "12345678"  # Robot router administrator password
  }
}
```

#### 1.2.2.2 Response: response_connect_wifi

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_connect_wifi",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success
                           # fail_no_wifi_band: Wi-Fi band not specified
                           # fail_no_wifi_ssid: SSID not specified
                           # fail_no_wifi_password: password not specified
                           # fail_no_router_admin_password: administrator password not specified
  }
}
```

### 1.2.3 Query Wi-Fi Connection Status

#### 1.2.3.1 Request: request_wifi_connection_status

This protocol is used by the client to send a Wi-Fi connection status query request to the robot router. After receiving the request, the router feeds back the core status information of the currently connected Wi-Fi, including the associated SSID, signal strength, and connection result, supporting the client in real-time perception of the device's network connection status. The client initiating a Wi-Fi connection status query must carry the robot router administrator password to complete identity verification.

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_wifi_connection_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "router_admin_password": "12345678"  # Robot router administrator password
  }
}
```

#### 1.2.3.2 Response: response_wifi_connection_status

After receiving the query request, the robot router returns the current actual Wi-Fi connection status for client-side parsing, display, or subsequent business processing.

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_wifi_connection_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "ssid": "Limx-Guests",
      "signal": -56,        # Unit: dBm
      "result": "success"   # success
                            # fail_disconnected
  }
}
```

### 1.2.4 Enter Ready State

The robot slowly assumes a ready posture.

#### 1.2.4.1 Request: request_prepare

Controls the robot to enter a standing state.

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_prepare",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": { }
}
```

#### 1.2.4.2 Response: response_prepare

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_prepare",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success, fail_motor: motor error
  }
}
```

### 1.2.5 Control Robot Walking

#### 1.2.5.1 Enter Walking Mode

The robot enters walking mode and can receive velocity commands.

#### 1.2.5.2 Request: request_set_walk_mode

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_set_walk_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 1.2.5.3 Response: response_set_walk_mode

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_set_walk_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success, fail_motor: motor error
  }
}
```

### 1.2.6 Control Robot Walking

In mobile operation mode, control the robot to walk through this protocol (requires > 10 Hz command issuance). Please note that in whole-body operation mode, this protocol interface is invalid.

#### 1.2.6.1 Request: request_set_walk_vel

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_set_walk_vel",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "x": 0.0,   #  Forward/backward velocity ratio, value range [-1, 1]
    "y": 0.0,   #  Lateral walking velocity ratio, value range [-1, 1]
    "yaw": 0.0  #  Rotational angular velocity ratio, value range [-1, 1]
  }
}
```

#### 1.2.6.2 Response: response_set_walk_vel

This message is returned when command execution fails; no response is returned on successful execution.

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_set_walk_vel",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": "fail_motor"  # fail_imu: IMU error, fail_motor: motor error
  }
}
```

#### 1.2.6.3 Message Push: none

### 1.2.7 Enter Damping Mode

All robot motors stop active motion, with noticeable damping when swung.

#### 1.2.7.1 Request: request_damping

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_damping",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 1.2.7.2 Response: response_damping

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_damping",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: motor error
  }
}
```

### 1.2.8 Enter Zero Torque Mode

All robot motors stop active motion, with no damping when swung.

#### 1.2.8.1 Request: request_zero_torque

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_zero_torque",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 1.2.8.2 Response: response_zero_torque

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_zero_torque",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: motor error
  }
}
```

### 1.2.9 Enter Standing Command

<callout emoji="💡"><p>Interface Function: Starts robot operation. After the robot is powered on, calling this interface transitions the robot into the standing state.</p><p>Parameter mode: [lying: robot is lying on the ground    hanging: robot is suspended  ]</p><p>Return: Returns after the robot has successfully stood up.</p><p>Requirement Link: <cite doc-id="G3UKwBUpXifBUQkPPllcOnCzn1e" file-type="wiki" title="【PRD】启动与回收机器人产品需求文档_V1.0" type="doc"></cite></p></callout>

#### 1.2.9.1 Request: request_standup

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_standup",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "mode": "lying" // "lying": robot is currently lying/sitting  or
                      // "hanging": robot is currently suspended
                      // If there is no "mode" field, the default robot state is "sitting"
  }
}
```

#### 1.2.9.2 Response: response_standup

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_standup",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: motor error
                          # fail_invalid_cmd: parameter error
                          # fail_invalid_mode: robot state error
                          # fail_timeout: execution timeout error
  }
}
```

### 1.2.10 Enter Lying Down Command

#### 1.2.10.1 Request: request_lie_down

<callout emoji="💡">
This interface can be called in Walk state
</callout>

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_lie_down",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

#### 1.2.10.2 Response: response_lie_down

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_lie_down",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor: motor error
  }
}
```

### 1.2.11 Whole-Body Teleoperation

#### 1.2.11.1 Switch Whole-Body Teleoperation Mode

##### 1.2.11.1.1 Request: request_set_wbt_mode

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_set_wbt_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      # 0: Exit whole-body teleoperation mode
      # 1: Enter WBT four-point control mode (not supported yet)
      # 2: Enter WBT joint control mode
      "mode": 0 
  }
}
```

##### 1.2.11.1.2 Response: response_set_wbt_mode

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_set_wbt_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success"  # success: Success, fail_motor: Motor error
  }
}
```

##### 1.2.11.1.3 Message Push: none

#### 1.2.11.2 WBT Joint Control Command

##### 1.2.11.2.1 Request: request_set_wbt_joint_pose

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_set_wbt_joint_pose",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "joint_q": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
                0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
                0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
    "base_pos":         [0.0, 0.0, 0.95],
    "base_quat":        [0.0, 0.0, 0.0, 1.0],
  }
}
```

##### 1.2.11.2.2 Response: response_set_wbt_joint_pose

Note: Feedback only when there is an error.

##### 1.2.11.2.3 Message Push: none

### 1.2.12 Robot Dance

#### 1.2.12.1 Switch Robot to Dance Mode

##### 1.2.12.1.1 Request: request_enter_dance_mode

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_enter_dance_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    # 0: Exit dance mode
    # 1: Enter dance mode 
    "mode": 0
  }
}
```

##### 1.2.12.1.2 Response: response_enter_dance_mode

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_enter_dance_mode",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

#### 1.2.12.2 Get Dance List

##### 1.2.12.2.1 Request: request_get_dance_list

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_get_dance_list",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 1.2.12.2.2 Response: response_get_dance_list

```JSON

    "accid": "HU_L04_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",
                "duration": 10
            },
            {
                "id": "DAN-08",
                "index": 1,
                "name": "\u4f4e\u4fd7\u5c0f\u8bf4",
                "english_name": "Pulp Fiction Dance",
                "rc_mapping": "pulp_fiction_dance",
                "duration": 10
            }
        ]
    }
}
```

#### 1.2.12.3 Robot Dancing

##### 1.2.12.3.1 Request: request_dance

<callout emoji="💡">
Execution prerequisite: Currently in action library mode
</callout>

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_dance",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "name": "one_and_only_dance"  # Dance name from the rc_mapping field
  }
}
```

##### 1.2.12.3.2 Response: response_dance

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_dance",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

##### 1.2.12.3.3 Message Push: notify_dance

This message is pushed after the dance is completed or if execution fails during the process.

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "notify_dance",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

### 1.2.13 Robot Action Library

#### 1.2.13.1 Action Interruption

##### 1.2.13.1.1 Request: request_interrupt_action_joystick

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_interrupt_action_joystick",
  "timestamp": 1779355330784,
  "guid": "32cef03a-5563-4b21-9bbb-3e65a8c9ae9e",
  "data": {}
}
```

##### 1.2.13.1.2 Response:

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_interrupt_action_joystick",
  "guid": "32cef03a-5563-4b21-9bbb-3e65a8c9ae9e",
  "timestamp": 1779355330784,
  "data": {
    "result": "success"
  }
}
```

#### 1.2.13.2 Get Action Library Status

<callout emoji="💡">
Interface Description:  
(1) After the robot enters the action library, whether it is in action library/atomic execution/dance mode, "action_library_mode": "action_library"  
(2) When the robot is executing an atomic action or dancing, "action_library_state": "running"
</callout>

##### 1.2.13.2.1 Request: request_get_action_library_status

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_get_action_library_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 1.2.13.2.2 Response: response_get_action_library_status

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "get_action_library_status",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "action_library_mode": "action_library" // or "remote_control"
      "action_library_state": "running"       //or "idle"
      "result": "success" # fail_motor
  }
}
```

#### 1.2.13.3 Switch Robot to Action Library Mode

##### 1.2.13.3.1 Request: request_set_motion_engine

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_set_motion_engine",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    # 0: Exit action library mode
    # 1: Enter action library mode 
    "mode": 0
  }
}
```

##### 1.2.13.3.2 Response: response_set_motion_engine

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_set_motion_engine",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

#### 1.2.13.4 Execute Action Library

##### 1.2.13.4.1 Request: request_action_sync

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_action_sync",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "name": "one_and_only_dance,this_way_please"  ,
                                    # name: multiple dances/multiple actions/mix of dances and actions, separated by ","
      "music": "bgm1.wav,bgm2.wav,"   # Optional, only supports .wav format files                             
  }
}
```

##### 1.2.13.4.2 Response: response_action_sync

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "response_action_sync",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
      "result": "success" # fail_motor
  }
}
```

#### 1.2.13.5 Get Action Library List

##### 1.2.13.5.1 Request: request_get_atomic_motion_list

```JSON
{
  "accid": "HU_L04_01_001",
  "title": "request_get_atomic_motion_list",
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {}
}
```

##### 1.2.13.5.2 Response: response_get_atomic_motion_list

```JSON
{
    "accid": "HU_L04_01_001",
    "title": "response_get_atomic_motion_list",
    "guid": "746d937cd8094f6a98c9577aaf213d98",
    "timestamp": 287883835,
    "data": {
        "result": "success",
        "motion_list": [
            {
                "id": "MON-01",
                "rc_mapping": "greeting1",
                "duration": 7,
                "motion_index": 0,
                "motion_name_cn": "侧身打招呼",
                "motion_name_en": "Greeting1"
            },
            {
                "id": "MON-02",
                "rc_mapping": "greeting2",
                "duration": 9,
                "motion_index": 1,
                "motion_name_cn": "抬腿打招呼",
                "motion_name_en": "Greeting2"
            }
            ......
        ],
        "count": 2
    }
}
```

### 1.2.14 Global Message Protocol Interface

### 1.2.15 Robot Status Information

Robot status information is periodically reported through this protocol, including the following content:

- `accid`: Robot serial number
- `title`: notify_robot_info
- `timestamp`: The timestamp when the message is sent, in milliseconds
- `guid`: The guid value of the message, uniquely identifying this message
- `data`: Contains the message content, example:

  ```JSON
  {
    "accid": "HU_L04_01_001", 
    "title": "notify_robot_info", 
    "timestamp": 1672373633989,
    "guid": "746d937cd8094f6a98c9577aaf213d98",
    "data": {
      "result": []
    }
  }
  ```

#### 1.2.15.1 Battery Data

```JSON
{
  "accid": "HU_L04_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"
                    }
                ]
            },
    ]
  }
}
```

| Field | Meaning |
|-|-|
| bmsconn | Battery connection status: [OFF: Not connected, ON: Connected] |
| bat_chg | Battery charger status: [OFF: Not connected, ON: Connected] |
| bat_off | Battery pre-shutdown status: [OFF: Power off after 1s, ON: Normal] |
| bat_prt | Battery fault code: [0: Normal, non-zero: Abnormal] |
| bat_vol | Battery real-time voltage, unit: mV |
| bat_cur | Battery real-time current, unit: mA |
| battery | Battery charge percentage 0\~100 |
| bat_temp0 | Battery temperature 0\~100, unit: x10℃ |
| bat_temp2 | Battery temperature 0\~100, unit: x10℃ |
| bat_temp4 | Battery temperature 0\~100, unit: x10℃ |

#### 1.2.15.2 Joystick Information Data (Only included in Lite models)

```JSON
{
  "accid": "HU_L04_01_001", 
  "title": "notify_robot_info", 
  "timestamp": 1672373633989,
  "guid": "746d937cd8094f6a98c9577aaf213d98",
  "data": {
    "result": [
        ......
        {
                "level": 0,
                "name": "peripheral",
                "message": "OK",
                "hardware_id": "peripheral",
                "values": [
                    {
                        "key": "joystickconn",
                        "value": "ON"
                    },
                    {
                        "key": "joysticksignal",
                        "value": "1"
                    },
                    {
                        "key": "joystickbattery",
                        "value": "2"
                    }
                ]
            },
    ]
  }
}
```

| Field | Meaning |
|-|-|
| joystickconn | Joystick connection status: [OFF: Not connected, ON: Connected] |
| joysticksignal | Joystick signal strength: [0-4, higher is stronger] |
| joystickbattery | Joystick battery information: [0:0%\~20%     <br/>                             1:21%\~40%     <br/>                             2:41%\~60%     <br/>                             3:61%\~80%     <br/>                             4:81%\~100%] |

#### 1.2.15.3 System Information

```JSON
{
  "accid": "HU_L04_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_L04_01_001"
                },
                
                { "key": "sdk_lite_led_enable", "value": "1" },
                { "key": "sdk_lite_led_has_params", "value": "1" },
                { "key": "sdk_lite_led_mode", "value": "0" },
                { "key": "sdk_lite_led_state", "value": "1" },
                { "key": "sdk_lite_led_color", "value": "4" },
                { "key": "sdk_lite_led_brightness", "value": "3" },
                { "key": "sdk_lite_leds", "value": "" },
                {"key": "walk_gait", "value":"walk"}
              ]
        }
    ]
  }
}
```

| Field | Meaning |
|-|-|
| version | Main controller version |
| ecm_version | Master station version |
| pms_version | Power distribution board version |
| motor_version | Motor version |
| sn | Robot serial number |
| robot_status | Robot current status |
| ability_running | Robot currently running controller |
| sdk_lite_led_enable() | Luna LED effect control switch: `0`=off, `1`=on |
| sdk_lite_led_has_params | Whether Luna LED effect parameters already exist: `0`=no, `1`=yes |
| sdk_lite_led_mode | Luna LED effect control mode: `0`=overall LED effect control, `1`=individual LED RGB control |
| sdk_lite_led_state | Overall LED effect status, valid when `mode=0` |
| sdk_lite_led_color | Overall LED effect color, valid when `mode=0` |
| sdk_lite_led_brightness | Overall LED effect brightness, valid when `mode=0`, range `0-5` |
| sdk_lite_leds | Individual LED RGB flat array string, valid when `mode=1`, e.g. `255,0,0,0,255,0` |

```JSON
    If mode = 1 for individual RGB control:
    { "key": "sdk_lite_led_mode", "value": "1" },
    { "key": "sdk_lite_led_state", "value": "" },
    { "key": "sdk_lite_led_color", "value": "" },
    { "key": "sdk_lite_led_brightness", "value": "" },
    { "key": "sdk_lite_leds", "value": "255,0,0,0,255,0,0,0,255" }
    When disabled:
    { "key": "sdk_lite_led_enable", "value": "0" },
    { "key": "sdk_lite_led_has_params", "value": "0" },
    { "key": "sdk_lite_led_mode", "value": "" },
    { "key": "sdk_lite_led_state", "value": "" },
    { "key": "sdk_lite_led_color", "value": "" },
    { "key": "sdk_lite_led_brightness", "value": "" },
    { "key": "sdk_lite_leds", "value": "" }
```

#### 1.2.15.4 Motor Status Information

```JSON
{
  "accid": "HU_L04_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!"
                    }
                ]
          }
    ]
  }
}
```

| Field | Meaning |
|-|-|
| level | Exception level [0:ok  1:warn  2:error] |
| name | Exception type |
| message | Level string |
| hardware_id | Hardware ID |
| values | All exception sets for this hardware |

### 1.2.16 Remote Controller Data

Robot remote controller data is reported through this protocol:

- `accid`: Robot serial number
- `title`: notify_joy_data
- `timestamp`: The timestamp when the message is sent, in milliseconds
- `guid`: The guid value of the message, uniquely identifying this message
- `data`: Contains the message content, example:

  ```JSON
  {
    "accid": "HU_L04_01_001", 
    "title": "notify_joy_data", 
    "timestamp": 1672373633989,
    "guid": "746d937cd8094f6a98c9577aaf213d98",
    "data": {
      "axes": [],     # Joystick axis data
      "buttons": []   # Button data
    }
  }
  ```

### 1.2.17 Protocol Interface Call Examples

#### 1.2.17.1 Python Example Implementation

- Environment preparation: Taking Ubuntu 20.04 as an example, install the following dependencies

  ```Python
  sudo apt install python3-dev python3-pip
  sudo pip install websocket-client==1.8.0
  ```
- Run the script

  ```Python
  python humanoid.py
  ```
- humanoid.py implementation

  <callout emoji="💡">
  - ACCID: Replace with the actual software SN
  - ROBOT_IP: Generally, 127.0.0.1 for simulation, 10.192.1.2 for real robot
  </callout>

  ```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', '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 == "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()
  
  ```

#### 1.2.17.2 Linux C++ Example

- Install dependencies: Taking Ubuntu 20.04 as an example, install websocketpp, nlohmann/json, and boost dependencies:

  ```Bash
  sudo apt-get install libboost-all-dev libwebsocketpp-dev nlohmann-json3-dev
  ```
- Compile the code

  ```Bash
  g++ -std=c++11 humanoid humanoid.cpp -o humanoid humanoid -lssl -lcrypto -lboost_system -lpthread
  ```
- Run the program

  ```Bash
  ./humanoid
  ```
- humanoid.cpp implementation

  ```c++
  #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', '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 == "damping") {
            send_request("request_damping");
        } else if (command == "zero") {
            send_request("request_zero_torque");
        }
  
        sleep(1);
  
        std::cout << "\nEnter command ('prepare', '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;
  }
  
  ```

<table><colgroup><col/><col/></colgroup><tbody><tr><td vertical-align="top"><b>Function Name</b></td><td vertical-align="top"><b>subscribeImuData</b></td></tr><tr><td vertical-align="top">Function Prototype</td><td vertical-align="top">void subscribeImuData(std::function&lt;void(const ImuDataConstPtr&amp;)&gt; cb);</td></tr><tr><td vertical-align="top">Description</td><td vertical-align="top">Subscribe to the robot's <b>IMU data</b> and call the specified callback function when new IMU data is received.</td></tr><tr><td vertical-align="top">Parameters</td><td vertical-align="top">cb: Callback function for processing new IMU data.</td></tr><tr><td vertical-align="top">Return Value</td><td vertical-align="top">None</td></tr><tr><td vertical-align="middle">Remarks</td><td vertical-align="top">The ImuData data structure prototype is as follows:<pre caption="&#xA;" lang="C++" wrap="false"><code>/**<br/> * @struct ImuData<br/> *<br/> * @brief Struct representing robot IMU data based on sensor feedback.<br/> *<br/> * This struct encapsulates IMU data, including accelerometer, gyroscope, and quaternion.<br/> */<br/>struct ImuData {<br/>  uint64_t stamp; // Timestamp in nanoseconds, typically indicating when this data was recorded or generated.<br/>  float acc[3];   // Stores IMU accelerometer data to track linear acceleration along three axes (X, Y, Z).<br/>  float gyro[3];  // Stores IMU gyroscope data to track angular velocity or rotation rate along three axes (X, Y, Z).<br/>  float quat[4];  // Stores IMU quaternion data representing orientation in 3D space (w, x, y, z).<br/>};<br/><br/>// Smart pointer type aliases<br/>typedef std::shared_ptr&lt;ImuData&gt; ImuDataPtr;<br/>typedef std::shared_ptr&lt;ImuData const&gt; ImuDataConstPtr;</code></pre></td></tr><tr><td vertical-align="middle">Code Example</td><td vertical-align="top"><pre caption="Code Block&#xA;" lang="C++" wrap="false"><code>#include &lt;thread&gt;<br/><br/>// Include limxsdk::Humanoid header to import the Humanoid class<br/>#include "limxsdk/humanoid.h"  <br/><br/>// Use limxsdk namespace to simplify references to the Humanoid class<br/>using namespace limxsdk;  <br/><br/>int main(int argc, char *argv[]){<br/>  // Get the singleton instance of the Humanoid class<br/>  Humanoid* robot = Humanoid::getInstance();  <br/><br/>  // Default robot IP address<br/>  std::string robot_ip = "127.0.0.1";<br/>  if (argc &gt; 1)<br/>  {<br/>    // If command-line arguments are provided, use them as the robot IP address<br/>    robot_ip = argv[1];<br/>  }<br/><br/>  // Initialize the communication runtime environment for the motion control algorithm<br/>  if (!robot-&gt;init(robot_ip))<br/>  {<br/>    // Exit if initialization fails<br/>    exit(1); <br/>  }<br/><br/>  // Subscribe to robot status updates with a callback function<br/>  robot-&gt;subscribeImuData([&amp;](const ImuDataConstPtr&amp; msg) {<br/>    // Process received ImuData data here<br/>    // Note: The callback function is called when ImuData is received<br/>  });<br/><br/>  // Infinite loop to keep the program running<br/>  while (true)<br/>  {<br/>    // Sleep for 1000 milliseconds<br/>    std::this_thread::sleep_for(std::chrono::milliseconds(1000)); <br/>  }<br/>  return 0;<br/>}</code></pre></td></tr></tbody></table>

## 1.3 Logs and Data Packets

The robot system automatically records: robot IMU data (ImuData), robot state data (/joint/state), and robot control data (/joint/cmd), and other important data. These data are crucial for robot motion control analysis. In addition, the robot also records runtime log data for troubleshooting and performance optimization when needed. When the computer is connected to the robot's Wi-Fi hotspot, you can access it by entering `http://10.192.1.2:8090` in the browser and download these data. This process provides convenience for robot monitoring, maintenance, and debugging.

![图片展示的是Luna系统中数据包可视化分析方法中数据包下载后的界面。在浏览器地址栏输入“10.192.1.2:8090”后，进入目录“/home/lmx/bigdata”，显示“3 items”，有“Upload”按钮，下方列出“bag”“log”“ota”三个目录，其中“bag”目录最后修改时间为“07 Nov 25 14:44 CST (52 seconds ago)”，“log”“ota”目录最后修改时间为“07 Nov 25 14:40 CST (4 minutes ago)”。该图与上下文介绍的下载`.bag`文件后使用PlotJuggler工具加载和分析数据包数据相呼应。](data:image/jpeg;base64,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### 1.3.1 Data Packet Visualization Analysis Method

- **Data Packet Download:** After downloading the `.bag` file, you can use the PlotJuggler visualization tool to load and analyze these packet data. It is particularly important to note that if you downloaded a `.bag.active` file, you need to use the following Shell command to reindex the `.bag.active` file and generate a new `.bag` file for PlotJuggler to load.

  ```Bash
  rosbag reindex your_file.bag.active
  mv your_file.bag.active your_file.bag
  ```
- **Visualization View:** Start the PlotJuggler visualization tool through the Shell command `rosrun plotjuggler plotjuggler -n`. Load the data packet and analyze the data as shown in the figure below.

  ![图片展示了Luna SDK中使用PlotJuggler可视化分析数据包的界面。界面左侧有“Load bag”按钮，用于加载数据包。右侧是数据可视化区域，显示了三条曲线，分别以红色、蓝色和绿色呈现，横轴为时间，纵轴为不同数据。该图对应文档中“Data Packet Visualization Analysis Method”部分，直观呈现了使用PlotJuggler加载和分析数据包后的可视化效果，辅助说明数据包可视化分析的操作及结果展示。](data:image/jpeg;base64,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Ys4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBtg1NxYs4rsXSs3ZhuLFnFdi6Vm7MBmq6aGspZqaqiZLBMxWSRvTNHNVMlRUKbse7HNswVV3CppJZaqeqeu1yTa1hizzSNF/xXx5J5C2bixZxXYulZuzDcWLOK7F0rN2YDbIrFdvmu2FrxbqV0baiso5qeNZFVGo57FaiuVEVcs115IptbixZxXYulZuzDcWLOK7F0rN2YCu2+HEdHdFuaYcwxJc3RMiWpkudQ9zWtaiZMzgXQTVrRuWa61PcsWJJqy4VVZY8MVvwgkbZqaoq5XRs2tFRMlWBdLPPXmiZZeMn9xYs4rsXSs3ZhuLFnFdi6Vm7MbprmmJiNuXjE+jpRiVURVTH+aLTvifOGqy+41jY1jLJhprGpkjUuU6IieT/YEnFJPNEySrZFHUvRHSsicrmNevCjVVEVUzzyVUT9SGtuLFnFdi6Vm7MNxYs4rsXSs3ZjDmrd72PLBd7pPcZWVlNVz5bc+jq5IElVEyRXI1URV+s0u5ZYf0q+dKTdYuO4sWcV2LpWbsw3FiziuxdKzdmAp3cssHjqb2qc6TdYtlhs9BYbXDbrTTtp6SHPRYiqutVzVVVdaqq+NTLuLFnFdi6Vm7MNxYs4rsXSs3ZgNs0b5aaK+Wuot10gbPSTtyexdX1oqL4lRclRU4D3uLFnFdi6Vm7MNxYs4rsXSs3ZgKjvJu207j363v4My0dr0Ytu0fJt2jpft4S1WO0UVitcFutcDYKSFMmsTX9aqq8Kqq61VTJuLFnFdi6Vm7MNxYs4rsXSs3ZgPF7t6XS2vpVldCqvZI2RqIui5j0e1cl4UzamohvgG8/Ci16X2Hb1h2j5AmWjpaXBp8OZObixZxXYulZuzDcWLOK7F0rN2YCtswxdm0FwpEvsW1VrpXy/6Cmecnxsu/1cJv2+xVkVZQz3C5pVNomObCxlOkWtW6OarmuerPyEruLFnFdi6Vm7MNxYs4rsXSs3ZgNTFdsfeMPVtDC5rZZWpoK7gzRyOTP+Bw+7bF2JXXKtnsLa6zwVy51dPS1zEikVeHRTSTJq5rqXPLM73uLFnFdi6Vm7MNxYs4rsXSs3Zj1YfCdCji6qIqi9875XtfVMdEOFeBpV6dNUxOrK3rE9Kh4ItlywbYo7XaMJO2tHackj7lEr5XrwucuX1J/Ann3fE72ObHhhkb1TJr318bmtXyqia1J7cWLOK7F0rN2YbixZxXYulZuzGuVYf9Gn/f+5niK/6lX+39rUwpbH2fD1FQzOa6WJq6at4M1crly/iQFmbiHDtClsgssdwp4Xv2qZlW2LNquVdaO8etS1bixZxXYulZuzDcWLOK7F0rN2YRwyq9c4lMVaU3m99eeeUxO2SeDRamKJmNGLRa2rLpieiFVvj7vfLXUW654OSeknREexblGnAuaKiomaKioioqeNCKoLVeKe6Utwq7BcLlU0jXNpnVt4iekGaZKrURqJmqatJc1+sv+4sWcV2LpWbsw3FiziuxdKzdmHKsL+jTvr/ecRX/AFav9v7URhagr46663O6xRwVFe+PKGN+noNY3JM18a6zWq6a8WrElwuFrt8dwp65kenHt6ROY5iaKa11ZZFg3FiziuxdKzdmG4sWcV2LpWbsw5bVxlVc0xMTERMZ2tFrRrvlaNpyanQimJmLTe+V7ze+y22diD+GcSclf+Ix+4fDOJOSv/EY/cTm4sWcV2LpWbsw3FiziuxdKzdmHKsL+jTvr/ecRX/Vq/2/tV+kprxdcSW+4XS3x2+noWSaEe3pK57nporrTVlkWsjpZbtb6qijvdFb4I6yZaeF1JWPnXTSN8nfI6JmSaMbtea68tRInLHx5xpjKIiItERfpmdszOuZ2umFhRhxOd5nOZndst0Pzy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vsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sN9mHOP7R6ZH1haS8JoELvsw5x/aPTI+sbFBfbRcZ9pt91oKqbLPQgqGPd/BFJZbpIAAAAAAMVXUwUdNJUVc0UFPGmk+WV6Na1PKqrqRAMpHVVylbcVoaC2V1yqmRNnkZTbU1I2OVUarnSPYmtWuyRFVe9XyG/FIyWNkkT2vjeiOa5q5oqLwKimPCnhxfebqH1tWBqbpvXJO8efo/xxum9ck7x5+j/HL8AKDum9ck7x5+j/ABxum9ck7x5+j/HL8AOcx3a5SXGehZha8LVQxRzyM22k71j1ejVz2/LWsb/4fWhsbpvXJO8efo/xySlqnUWNcQVEdNNVPZaaDRhhTNz126s1IV+yX/GEd9kmutlq5LdMuSxMi1wp4lb5frz4QJK13BK9tQjqeopaimlWCennREfG9ER2S6Kqi5tc1UVFVFRUN0jaJc8TYsXy3GP2OmJIAAABX7thG03SudV1MciTPy09B6ojstWtCwH8c5GNVzlRrUTNVVckRDni4VGLFsSLx1u2BwjFwKtLCqmmepXrfhC10D0fTsVXJwLKyOX/ANzVLEyWuYxGsuM7WomSIkUSIn/4GGjq6eupo6miniqKeRM2SxPR7HJ9SpqUzFowqMLKimI7ITFx8TGm+JVNXbN393RcOM6jzcXUIx17vEtbVU1shvNydSuayd9OykYxj1ajkbnIrM10XNXVnlmmfCSQwD8sxVzo32OmNuSP+EcVcTYh+3bfxR8I4q4mxD9u2/il9AFC+EcVcTYh+3bfxR8I4q4mxD9u2/il9AFC+EcVcTYh+3bfxR8I4q4mxD9u2/il9AHOqC/Yir4HTUlqxDJG2WSBVztyZPje6N6a5PE5rk+vLVqM0l0xRFG6R9mxFoNRXLo/B7lyTyI2RVX9SIqiiulxt2E6pLNbpq2tlulyRmgzNsf+mz9873GbAN2xE524cSW2rzXNY6t0eSeXRd/yUDNQ3KqrqKnq6W7VD6eeNssbtri75rkzRfieRT3OtVUMSOor55YtJrlYrI0RVaqKnA1F4UQhsCeA+Hubqf1TScA/PIAAfbv5PDNr2HrCxdatWpT+ZlLnY/D2+c2UHraspf5Oqq7Ycw+q8K7o9olLKy8W2x45uUl6r6a3w1VupGwS1UiRMkdHLUabUc7JM0SRi5Z56wLyCu7+cJ8qLF0hD1hv5wnyosXSEPWAsQK7v5wnyosXSEPWG/nCfKixdIQ9YCxAru/nCfKixdIQ9Yb+cJ8qLF0hD1gLECu7+cJ8qLF0hD1hv5wnyosXSEPWAsQK7v5wnyosXSEPWG/nCfKixdIQ9YCxAru/nCfKixdIQ9Yb+cJ8qLF0hD1gLECu7+cJ8qLF0hD1hv5wnyosXSEPWAsQK7v5wnyosXSEPWG/nCfKixdIQ9YCxAru/nCfKixdIQ9Yb+cJ8qLF0hD1gLECu7+cJ8qLF0hD1hv5wnyosXSEPWAsQK7v5wnyosXSEPWG/nCfKixdIQ9YCxAru/nCfKixdIQ9Yb+cJ8qLF0hD1gLECu7+cJ8qLF0hD1hv5wnyosXSEPWAsQK7v5wnyosXSEPWG/nCfKixdIQ9YCxAru/nCfKixdIQ9Yb+cJ8qLF0hD1gLECu7+cJ8qLF0hD1hv5wnyosXSEPWAsQK7v5wnyosXSEPWG/nCfKixdIQ9YDXvnh7Y+bK/wBbSERsmeDNPzta/b6c2H3i23zHNtlstdTXCGlt1W2eWlkSVkbpJafQarm5pmqRvXLPPV+o19kzwZp+drX7fTgShm2N/Bh/ONw9smMJm2N/Bh/ONw9smAs4AAHJtkGC312JcSpiBzEZb7CyptqyP0dpkV0unLH5HorYkzTWmpPGdZNG5We2XSSnkuduo6ySndpwuqIGyLE7ytVUXJfrQkxdYm3zruoeK651dgzDVNdJ2ZT1dBFeI9PJWteiKrZMvio52iiovCi5eMrUVPRvv8dgkbG7BqYhlgZTqv8Ao6qlGj0hy4NBJdJdHg0kyy1ZHYprTbp0rEmoKSRKxEbUo+Fq7eiJkiPzTvsk1a8zE6w2d1oS0utVAtrRMko1p2bSiZ5/Ey0eHXwGpnOZtr+3lbLtZiLREdEe/v4OP2GChut0tNpvix1GFo5bslDHUPzik2uZjY9ark7QYsmj5ETNOA6PsVT1FTsfWaWqkklesSoySRVVz40e5I3Kq8ObEaufjJqssVorbdFb6y1UFRQQ5bXTS07HxMy4MmqmSZfUSEbGxsayNqNY1MmtamSInkQRlFvk9c9a7b/I7H9ABAKZivw4sXN1d62kLmUzFfhxYubq71tIBB7ItdVWzAl+rberm1UNHK+NzeFq6K98n6uH9hVsHbHuF6/YzoqOSjjqI7lTRVFRU55yvlVuemjuFFRXOy8mtPKdHnhjqIJIZ2NkikarHscmaOaqZKip5Dl6bEk9C58WHcZX+025XK5lHFKrmR5rmqN1pqAs7NjnCO5GwzYetUi6CNc9KVjVcuWtdSal/UQOwgq0tJiWz08z57Za7vNTUb3O0tGPUugi+PJV+81nbF17karJtkXEj4nanNSRUzTyZ6RfMJYct+FbHBarTG5lPHm5XPXN8jl4XOXxqoEwfPn5W/yTDH+/Uf4Rn0Gc52W9jyXH9VYYt2MpKKjdM6oflpPVHaGSNTgz71da8H1gfKGDZb9Ff6ZcKLVpdVXKNKVFVy/rTgVvlz1eU+2cFuv78P0y4sZSMuuX5xKZc25eLPxaXly1eQxYNwdZMH0G5bHRtiVUTbJnd9LKvlc7x/q4PIhYQIXG/gXf+b6j1bjl+H/+wbb/AOmj/wDah2eeGOogkhnjZLDI1WPY9qOa5qpkqKi8KKhS5cCvjm0Lbcm09FmqpFJTbY5iKuei1yORMk4EzRVy8al2JtXPYj8BKT/1NZ7VKXE5lSYNw9T00cT7PQVL2pk6aopo3ySL43Odo61VdfuM29PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3Rwc43p4c4gtHocfVG9PDnEFo9Dj6oyM3RysbI6Uy4SrllSFaxGKtCr8tJKn/APZKzP8ApaejwFf3p4c4gtHocfVNigsVot023W+1UFLNllpwU7GO/iiASRy3Zrtcdwls809fanQ0u2yPtNyrVpmViZJrRyKnfN8WerX/AB6kR91stqu6RpdrZQ1yR/E3TAyXR/VpIuRmYu1E2cYjxlUVVNhimw3dWYVtM1snnRKlkc6I+J6tRmnJrVFyXXnmqGvdNk3E1XS4fZTyJbJqu2OrHSMigVJ5Ue5qJ+fe1qM71HLkqu77UdZueB7Fc71QXGuo4pkoqd1NFSPijdTo1VRc9BWrrTLVkqZEtcLJarlTwwXG2UNXBD/s456dkjWf7qKmSfsLOe/3943JGXzs++9xfE+yHitlxo6OB8VtqUtcNYrGtp3sqJXcKK+WRESPVlmxVUxbJ2Jrxc6bEFsrLnT2aCmtENQtCscb3Vr5G5va17lzyaurvTtdfYLPcI4I6+02+qjp00YWzUzHpGnkaipq/YLlYbPdFhW52qgrFhTKPdFOyTQTyNzRcv2Eqi8THb6/O5aZtMT2ent4oHANTNK+phkvdLWxRU1LoUMcbUko84kzR6oua6XCmZasKeHF95uofW1Z4paCjpJ5pqWkp4Zpkakj442tc/RTJukqJryTUmfAe8KeHF95uofW1ZuqbzdimLRZrbKVvZKuH6589TpQXeiayFsytiVVnbm5WJqcuWpM88vEe9lCpp57fbqGWojWikutLBcmJJlowvVVRsmS6muXQRc+FF+sudVS09W1jaqCKZrHtkakjEcjXtXNrkz4FRdaL4jBNardOlYk1BSSJWIjanThau3oiZIj8077JNWvMxGUW67+WXg1Oc36refuquxmyKmqMUUNu0Us9JdFio2MXNkabVG57GeRqPV2pNSLmhdzXt9DSW2jjpLdSwUlLGmTIYI0jY1PqampDYNdHcOd4g32d0O4bz/gL/suj3R8K7d/86q0dDa//qzz+of62f7C/wA2TEtK6txpiCnjqZqV77TQaM0K5OYu3VmtCv2SwYwkvskN1vVXHboXZrKyXXMniRvk+vPgIPGE/hbd+Jd8W4PhX4Rbt24NPafktPo6On33xdHPPx5nKNkVlusmO63EF4fbb9TNlgalH8IuirKBUy/2caLk5FzR2Xj/AFZqdnokyxNixPJcY/Y6Y/k+H7NUXFLhPaLdLXoqKlS+mY6VFTgXSVMxGVUSbJhyK03astF/2RLlTX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SF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAADfBcuSF989RdoG+C5ckL756i7QAA3wXLkhffPUXaBvguXJC++eou0AAN8Fy5IX3z1F2gb4LlyQvvnqLtAAHwoAAP/2Q==)

### 1.3.2 Log and Diagnostic Tracking Point Data

The following figures show the log and tracking point structured data respectively. They can be used for troubleshooting and performance optimization when needed.

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## 1.4 Robot Software Upgrade

We enter the robot management page through the browser and select the locally pre-downloaded robot software version for upgrade. The specific steps are as follows:

- Please select and connect to your robot's Wi-Fi hotspot, password: `12345678`

1. Access the management page:

   - Enter in the browser address bar: [http://10.192.1.2:8080](http://10.192.1.2:8080/) to enter the robot management page.
2. Select and upgrade software:

   - Select "Version Management -> Browse -> Upgrade" in sequence.
   - After the upgrade is completed, the robot's main control computer will automatically restart.

# 2. Motion Training Method Reference

## 2.1 Training Method Selection

| Method | Applicable Scenarios | Main Process | Prerequisites |
|-|-|-|-|
| **Bon & Flux** | Platform accessible, wishing to reduce local environment setup work | Bon retargeting → Flux training → cloud desktop/local simulation → export | Bon, Flux accounts and valid computing power quota |
| **Local Offline Training** | Data cannot leave the domain, platform unreachable, or need for high-frequency parameter tuning iterations | GMR local retargeting → LimxMimic local training → local simulation → export | Ubuntu, NVIDIA GPU, official repository access permissions |

```mermaid
flowchart LR
A[Raw Motion Capture Data] --> B{Select Training Method}
B -->|Platform| C[Bon Retargeting]
C --> D[Flux Training]
B -->|Local| E[GMR Retargeting]
E --> F[LimxMimic Training]
D --> G[Policy Playback and Simulation]
F --> G
G --> H[Unified Export Deployment Package]
H --> I[8080 Upload]
I --> J[SDK Call and Real Robot Verification]
```

<callout emoji="❗">
The final deployment specifications for both routes are the same. Training, playback, and export must use the motion data and checkpoint corresponding to the same task. Do not mix products from different motions, different code versions, or different task configurations.
</callout>

## Platform Training Based on BON & Flux Training

### 2.2.1 User Business Full Process

<whiteboard token="BvxnwS7NEhm1lvbj5KjcS0vXnwf"></whiteboard>

Note: When Bon is not online, retargeting can be completed through local scripts

### BON & Flux Training Product User Manual

<table><colgroup><col/><col/><col/><col/><col/><col/></colgroup><thead><tr><th vertical-align="top">Product</th><th vertical-align="top">Description</th><th vertical-align="top">Status</th><th vertical-align="top">Timeline</th><th vertical-align="top">Official Website</th><th vertical-align="top">Product User Manual</th></tr></thead><tbody><tr><td vertical-align="middle">LimX BON</td><td vertical-align="middle">BON is a full-process motion data pipeline management platform built for embodied intelligent robots, covering the complete data chain from motion capture upload, Retargeting, to quality assessment and training data export.</td><td vertical-align="middle"><b><code>In Development</code></b></td><td vertical-align="middle">Expected to launch in September</td><td vertical-align="middle"><a href="https://bon.limxdynamics.com">bon.limxdynamics.com</a></td><td vertical-align="middle"><cite doc-id="DTPMwS0OOiI1hVkzER9cZt4Bngb" file-type="wiki" title="LimX BON｜产品使用手册" type="doc"></cite></td></tr><tr><td vertical-align="middle">LimX Flux Training</td><td vertical-align="middle">Flux Training is a cloud-based algorithm training platform specifically built for embodied intelligence, providing ready-to-use GPU computing power with pre-installed mainstream simulation environments (such as Isaac Gym, Isaac Sim), and engineering adaptations, allowing <b>developers</b> to say goodbye to tedious configurations and focus on algorithm training and robot innovation research.</td><td vertical-align="middle"><b><code>Launched</code></b></td><td vertical-align="middle">Full capabilities available, model conversion launched on 9.3</td><td vertical-align="middle"><a href="https://flux.limxdynamics.com">https://flux.limxdynamics.com</a></td><td vertical-align="middle"><cite doc-id="Lx4jdTexeofu3kxbjh3ced6XnYe" file-type="docx" title="Flux Training｜产品使用手册" type="doc"></cite></td></tr></tbody></table>

## 2.3 Local Offline Training

### 2.3.1 Computer and Software Requirements

- Recommended Ubuntu 22.04, NVIDIA graphics card and available drivers.
- Minimum recommendation: 16-core CPU, 24 GB VRAM, 32 GB RAM; reserve at least 25 GB of disk space.
- Install Git, Git LFS, Miniconda or Anaconda.
- GitHub account needs access to GMR, Luna robot description repository, and official LimxMimic training repository.

<callout emoji="💡">
Testing confirms that the business training methods for Luna L03 and L04 are consistent; the current public export tool fixedly uses the 141-dimensional observation and 27-dimensional action of HU_L04_01 Parallel Deploy Gravity. The task name, robot configuration, and export tool must come from the same version of the official delivery package. Do not mix L03/L04 configurations on your own.
</callout>

### 2.3.2 Download Code and Prepare Directory

```bash
cd ~
git clone --branch limx --single-branch \
  https://github.com/limx-retarget/GMR.git GMR
git clone https://github.com/limx-luna/luna-beyondmimic.git whole_body_tracking
mkdir -p ~/data
```

Subsequently, use `~/GMR` uniformly for retargeting, and use `~/whole_body_tracking` for motion preparation, training, playback, and export. Place the original motion files in `~/data`, and try to use English for file names and paths without spaces.

### 2.3.3 Install GMR Environment

```bash
cd ~/GMR
git lfs install
git lfs pull
git config submodule.assets/luna-description.url \
  https://github.com/limx-luna/luna-description.git
git submodule update --init assets/luna-description

conda create -n gmr python=3.10 -y
conda activate gmr
python -m pip install -e .
conda install -c conda-forge libstdcxx-ng -y
```

<callout emoji="❗">
If the submodule shows `Permission denied` or `Repository not found`, it means the account lacks Luna description repository permissions. You should apply for permissions first. Do not skip the submodule or copy asset files of unknown versions.
</callout>

### 2.3.4 Determine Original Data Type

| Input | Processing Entry | Key Confirmation Items |
|-|-|-|
| Luna Retargeting NPY | Direct preview and training | Must be generated by the official GMR/Bon process, not any NumPy file |
| SMPL-X NPZ | `smplx_to_robot.py` | pose, root, trans and frame rate fields are complete |
| Ordinary BVH | `bvh_to_robot.py` | Confirm lafan1, nokov, fzmotion, soma or noitom format and actual frame rate |
| Xsens 3ds Max BVH | `xsens_bvh_to_robot.py` | Confirm displacement unit; centimeters use 0.01, millimeters use 0.001 |
| Video, FBX, CSV, etc. | Convert first | The current official process cannot read directly |

### 2.3.5 Retarget to Luna Motion

The following commands only execute the one corresponding to the data type:

```bash
conda activate gmr
cd ~/GMR
mkdir -p output

# Ordinary BVH example: modify format and motion_fps according to actual data
python scripts/bvh_to_robot.py \
  --bvh_file ~/data/walk.bvh \
  --format nokov \
  --motion_fps 50 \
  --robot limx_luna \
  --save_path output/my_motion.npy

# Xsens 3ds Max BVH example
python scripts/xsens_bvh_to_robot.py \
  --bvh_file ~/data/walk_xsens.bvh \
  --robot limx_luna \
  --bvh_format 3DSM \
  --scale 0.01 \
  --reset_to_zero \
  --save_path output/my_motion.npy
```

When the BVH type is unknown, you should first confirm the acquisition device and export template with the data provider. Incorrect format, frame rate, or unit often manifests as the robot moving sideways, body leaving the ground, or abnormal limb directions.

### 2.3.6 Preview Retargeted Motion

```bash
conda activate gmr
cd ~/GMR
python scripts/vis_robot_motion.py \
  --robot limx_luna \
  --robot_motion_path output/my_motion.npy
```

Confirm that the overall direction, limb posture, foot contact, and motion tail have no obvious abnormalities. In a pure SSH environment, you can temporarily skip the preview, but you must complete simulation verification after training.

### 2.3.7 Install LimxMimic Training Environment

```bash
conda create -n limxmimic python=3.10.15 -y
conda env config vars set PYTHONNOUSERSITE=1 -n limxmimic
conda env config vars set OMNI_KIT_ACCEPT_EULA=Y -n limxmimic
conda activate limxmimic

python -m pip install --upgrade pip
python -m pip install "setuptools==75.8.0" wheel
python -m pip install torch==2.5.1 torchvision==0.20.1 \
  --index-url https://download.pytorch.org/whl/cu118
python -m pip install --no-cache-dir "isaacsim[all,extscache]==4.5.0" \
  --extra-index-url https://pypi.nvidia.com

cd ~
git clone --branch v2.1.0 --depth 1 \
  https://github.com/isaac-sim/IsaacLab.git IsaacLab-2.1.0
cd ~/IsaacLab-2.1.0
echo "setuptools<81" > ~/isaaclab-build-constraints.txt
export PIP_CONSTRAINT=~/isaaclab-build-constraints.txt
export TERM=xterm
./isaaclab.sh --install

cd ~/whole_body_tracking
git submodule update --init --recursive
python -m pip install -e source/whole_body_tracking
```

GMR and LimxMimic use two independent Conda environments. Retargeting commands run in `gmr`, and training and export commands run in `limxmimic`.

### 2.3.8 Pre-training Check

```bash
conda activate limxmimic
cd ~/whole_body_tracking
python scripts/prepare_motion.py \
  --input ~/GMR/output/my_motion.npy \
  --output motions/my_motion_parallel_tail10.npz \
  --robot hu_l04_parallel \
  --linkage_report motions/my_motion_linkage_report.json \
  --force_tail
```

This step is used to explicitly check parallel linkage solving, tail frames, and kinematics results. The generated NPZ is a diagnostic intermediate file; the current recommended training, playback, and combined export still uniformly pass in the same trusted NPY, and the tool internally executes a consistent motion preparation process.

### 2.3.9 Start Training

```bash
conda activate limxmimic
cd ~/whole_body_tracking
python scripts/rsl_rl/train.py \
  --task=Tracking-Flat-HU-L04-Parallel-Deploy-Gravity-v0 \
  --motion_file ~/GMR/output/my_motion.npy \
  --motion_force_tail \
  --num_envs 4096 \
  --headless \
  --max_iterations 15000 \
  --logger tensorboard
```

When the training directory appears in the terminal and iteration information is continuously updated, it means training has started normally. When VRAM is insufficient, reduce `--num_envs` to 2048 or 1024 in sequence. Do not modify the task name and observation/action dimensions.

### 2.3.10 Playback and Export

```bash
# Playback the checkpoint from the same training run
python scripts/rsl_rl/play.py \
  --task=Tracking-Flat-HU-L04-Parallel-Deploy-Gravity-v0 \
  --checkpoint /path/to/model_14999.pt \
  --motion_file ~/GMR/output/my_motion.npy \
  --motion_force_tail \
  --num_envs 1 \
  env.commands.motion.debug_vis=false \
  env.scene.contact_forces.debug_vis=false

# Export the complete deployment package
python tools/offline_onnx_exporter/export_policy_and_reference.py \
  --checkpoint /path/to/model_14999.pt \
  --motion ~/GMR/output/my_motion.npy \
  --output_path exported/my_motion
```

## 2.4 Training Engineering, Adjustable Parameters and Interface Red Lines

### 2.4.1 Repository Directory Structure

The repository is divided into two major parts: `source/` is the training code installed as a Python package, and `scripts/` is the directly executable command-line tools. Daily configuration changes are in `source/`, and daily process runs are in `scripts/`.

```text
whole_body_tracking/
├── scripts/                         Command-line tools, execute directly
│   ├── rsl_rl/
│   │   ├── train.py                 Start training
│   │   ├── play.py                  Playback policy, also exports ONNX
│   │   └── cli_args.py              Training/playback command-line parameters
│   ├── solve_parallel_linkage.py    Solve closed-chain degrees of freedom
│   ├── npy_to_npz.py                Retargeting npy to training npz
│   ├── append_motion_tail.py        Add tail frames that maintain the terminal posture
│   ├── verify_motion_npz.py         Verify npz with forward kinematics (hard gate)
│   ├── dump_articulation_order.py   Print the canonical joint/rigid body order of the model
│   └── replay_npz.py                Directly playback reference motions in Isaac Sim
│
├── source/whole_body_tracking/whole_body_tracking/
│   ├── tasks/tracking/
│   │   ├── tracking_env_cfg.py      Total configuration for rewards, terminations, domain randomization, observations
│   │   ├── mdp/
│   │   │   ├── commands.py          Reference motion loading, error calculation, adaptive sampling
│   │   │   ├── rewards.py           Reward function implementation
│   │   │   ├── terminations.py      Termination condition implementation
│   │   │   ├── events.py            Domain randomization implementation
│   │   │   └── observations.py      Observation item implementation
│   │   └── config/hu_l04/
│   │       ├── parallel_env_cfg.py  Environment configuration for closed-chain variant
│   │       └── agents/
│   │           └── rsl_rl_ppo_cfg.py  PPO hyperparameters and network structure
│   ├── robots/
│   │   └── hu_l04_parallel.py       Closed-chain model actuator gains, armature, action scaling

│   └── utils/exporter.py            ONNX export and metadata
│
├── motions/                         Converted npz reference motions
├── logs/rsl_rl/                     Training products: checkpoint, TensorBoard, exported ONNX
├── export_specs/                    Offline ONNX export specification files
└── tools/offline_onnx_exporter/     Independent export tool not dependent on Isaac Sim
```

### 2.4.2 Configuration File Quick Reference

| Modification Target | Corresponding File |
|-|-|
| Rewards, termination thresholds, domain randomization | `tasks/tracking/tracking_env_cfg.py` |
| Curriculum sampling parameters | `MotionCommandCfg` in `tasks/tracking/mdp/commands.py` |
| Add a new reward function | `tasks/tracking/mdp/rewards.py` |
| PPO hyperparameters, network width | `config/hu_l04/``agents/rsl_rl_ppo_cfg.py` |
| Actuator stiffness and damping | `robots/``hu_l04_parallel``.py` |
| Observation items | `config/hu_l04/``parallel_env_cfg.py`, **but do not modify** |

---

### 2.4.3 Interface Red Line: Observation and Action Items Cannot Be Modified

<callout emoji="❌">
**It is forbidden to add, delete, or adjust observation items, observation order, action dimensions, and action order.** These contents constitute the fixed interface contract between the policy and the robot's lower-level controller. After modification, the policy cannot be correctly deployed.
</callout>

| Item | Reason for Not Being Modifiable |
|-|-|
| **Observation** | Each item and its order are written into ONNX metadata. The lower-level controller concatenates the input vector according to a fixed layout. Adding or deleting items or changing the order will cause input misalignment. |
| **Action** | The 27-dimensional actions correspond to specific motor slots respectively. Changing the width or order will cause control commands to be sent to the wrong joints. |

The current task `Tracking-Flat-HU-L04-Parallel-Deploy-Gravity-v0` uses **141-dimensional observation, 27-dimensional action**:

```text
command(54) + base_ang_vel(3) + projected_gravity(3)
            + joint_pos(27) + joint_vel(27) + actions(27) = 141
```

**Deploy** means that global position, state-estimated linear velocity, and sensorless link degrees of freedom that the lower-level controller cannot directly obtain have been removed; **Gravity** means that the gravity direction directly provided by the IMU is retained.

### 2.4.4 Reward Parameters

Rewards are a relatively safe adjustment entry, defined in `RewardsCfg` of `tracking_env_cfg.py`.

| Reward Item | Weight | std | Main Impact After Increasing |
|-|-|-|-|
| motion_global_anchor_pos | 0.5 | 0.3 | Torso world position fits more tightly, but at the cost of local posture degrees of freedom |
| motion_global_anchor_ori | 0.5 | 0.4 | More accurate torso orientation |
| motion_body_pos | 1.0 | 0.3 | More accurate limb positions, the main constraint for motion similarity |
| motion_body_ori | 1.0 | 0.4 | More accurate limb orientations |
| motion_body_lin_vel | 1.0 | 1.0 | Linear velocity and motion rhythm closer to the reference |
| motion_body_ang_vel | 1.0 | 3.14 | Rotation rhythm closer to the reference |
| action_rate_l2 | −0.1 | — | Smoother actions, less jitter, but slower response |
| joint_limit | −10.0 | — | Stronger avoidance of joint limits, may conflict with reference motions close to the limits |
| undesired_contacts | −0.1 | — | Reduce contact with parts other than feet and hands |

<callout emoji="💡">
**std is usually more worth prioritizing adjustment than weight.** The tracking reward adopts the `exp(−error² / std²)` form; the smaller the std, the stricter the constraint, and the larger the std, the higher the tolerance range. The six `motion_*` items define the task itself and are not recommended for deletion.
</callout>

### 2.4.5 Termination Conditions

Termination conditions are defined in `TerminationsCfg`, which directly determines whether the policy has the opportunity to learn the complete motion.

| Termination Item | Default Threshold | Meaning |
|-|-|-|
| time_out | 10 s (500 steps) | Normal end, not a failure |
| anchor_pos | 0.25 m | Maximum allowable deviation of torso anchor height from the reference |
| anchor_ori | 0.8 | Deviation of torso tilt from the reference |
| ee_body_pos | 0.25 m | Maximum allowable deviation of any end height of both ankles and both wrists from the reference |

You can use "threshold ÷ peak vertical velocity of the end" to estimate the fault tolerance window. For example, if the peak velocity is 2 m/s and the threshold is 0.25 m, the policy is only allowed to lag by about 0.125 seconds. When the completion rate of large leg lifts, jumps, or standing-up motions is persistently low, and the failure reason is concentrated in `ee_body_pos`, you can evaluate relaxing the threshold to 0.4–0.5 m.

### 2.4.6 Domain Randomization

Increasing randomization can improve real-robot robustness, but will reduce training speed and simulation tracking accuracy.

| Parameter | Default Range | Effect |
|-|-|-|
| physics_material static friction | 0.3–1.6 | Cover different ground friction conditions |
| physics_material dynamic friction | 0.3–1.2 | Affect sliding characteristics after contact |
| physics_material elasticity | 0.0–0.5 | Control ground contact rebound |
| add_joint_default_pos | ±0.01 rad | Simulate joint zero calibration errors |
| base_com | x ±0.025 m, y/z ±0.05 m | Simulate torso center of mass deviation, has a large impact on balance |
| push_robot interval | 1–3 s | Control external disturbance frequency |
| push_robot velocity | xy ±0.5 m/s, yaw ±0.78 rad/s | Increasing can improve anti-disturbance ability, but will interfere with fine motions |

### 2.4.7 Curriculum Sampling

Curriculum sampling is defined in `MotionCommandCfg`, used to determine from which time point of the motion each reset starts.

| Parameter | Default Value | Impact |
|-|-|-|
| adaptive_kernel_size | 1 | When 1, failures are only recorded at the current time point; when long motions are stuck at a fixed difficulty point, it can be adjusted to 5, allowing sampling to cover the process before entering the difficulty point |
| adaptive_uniform_ratio | 0.1 | Ensure all time periods have the minimum sampling amount, avoid computing power concentrated on a single difficulty point |
| adaptive_alpha | 0.001 | Control the update speed of the failure histogram; increasing makes the response faster but more volatile |
| pose_range / velocity_range | Subject to configuration | Control initial state disturbance during reset, increasing can improve robustness |

### 2.4.8 PPO Hyperparameters and Network

Defined in `config/hu_l04/``agents/rsl_rl_ppo_cfg.py`. The default configuration is suitable for most motions, and modification is not recommended without clear evidence.

| Parameter | Default Value | Description |
|-|-|-|
| Network | [512, 256, 128], ELU | Only consider widening when the observation dimension increases significantly; the current observation dimension is prohibited from modification |
| num_steps_per_env | 24 | Number of sampling steps per environment per round |
| learning_rate | 1e-3, adaptive | The actual learning rate is scheduled by desired KL feedback |
| desired_kl | 0.01 | Main update step size control parameter; smaller is more stable but slower training |
| entropy_coef | 0.005 | Increasing enhances exploration, too large will cause action jitter |
| gamma / lam | 0.99 / 0.95 | Discount factor and GAE parameter |
| max_iterations | 30000 | Can be overridden from the command line, in practice 15000 rounds usually enter the convergence interval |

### 2.4.9 Actuator Gains

Actuator gains are defined in `robots/``hu_l04_parallel``.py`, uniformly calculated from natural frequency, damping ratio, and armature in the manufacturer's MJCF:

```python
NATURAL_FREQ = 10 * 2 * pi   # 10 Hz
DAMPING_RATIO = 2.0

stiffness = armature * NATURAL_FREQ ** 2
damping = 2 * DAMPING_RATIO * armature * NATURAL_FREQ
```

- **NATURAL_FREQ increase**: Tracking is stiffer and more accurate, but the real robot is more prone to jitter.
- **DAMPING_RATIO increase**: The system is more stable, but the response is more sluggish.
- **soft_joint_pos_limit_factor** defaults to 0.9; it can be carefully increased when reference motions need to be close to the limits.

<callout emoji="❗">
Adjusting gains should modify the unified constants. Do not arbitrarily change values joint by joint, so as not todisrupt the relative relationship between individual joints. Any parameter adjustment result must re-complete simulation and real-robot safety verification.
</callout>

# 3. Dance Motion Simulation Cloud Desktop Verification

## 3.1 Cloud Desktop Creation

1. Register and log in to Flux Training ([https://internal.limxdynamics.com/user/login](https://internal.limxdynamics.com/user/login))
2. Recharge the account (for redemption codes, please contact LimX Dynamics sales colleagues)
3. Select "Cloud Desktop" and click Add

![这张图片是Luna SDK开发指南中“云桌面创建”步骤里的对应页面，页面左侧是功能导航栏，“Cloud Desktop”选项呈高亮选中状态；页面主区域标题为“Cloud Desktop”，配有运行云桌面的示意图，下方有说明文字介绍云桌面的作用是运行虚拟桌面实例，负责计算、存储和资源调度；页面底部还有蓝色的“Create”按钮，用于创建新的云桌面，对应步骤3中“选择‘Cloud Desktop’并点击Add”的操作指引。](data:image/jpeg;base64,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1. Create a new cloud desktop and select configuration parameters

   1. Computing power: Select as needed, 3 tiers available, 5880 16G/24G/48G
   2. Image system: Scroll to the bottom and select the image dedicated to Luna secondary development
   3. System disk: Select as needed, 2 tiers available, 100G and 200G
   4. Auto shutdown: Select as needed, the identification criterion is whether the mouse is moved

   ![这张图片是创建云桌面的操作界面，对应文档中创建云桌面流程里的“Create Cloud Desktop”页面。页面左侧导航栏已选中“Cloud Desktop”选项，右侧为云桌面配置区域，包含“Cloud Desktop Name”输入框、“Resource Specification”等配置项，界面还呈现了系统磁盘、自动关机等配置相关内容，底部有“Create”和“Cancel”按钮，该界面用于进行云桌面创建的参数设置，匹配文档中步骤4提及的创建新云桌面并选择配置参数的操作内容。](data:image/jpeg;base64,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2. Create and power on, wait for boot

![这张图片是Luna SDK开发指南中云桌面创建步骤里的相关界面，对应Luna二次开发专用的云桌面配置信息展示界面。界面明确标注该云桌面为Luna二次开发专用，基于Linux 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![图片展示的是Luna Training Simulation的云桌面创建界面。界面中显示“Luna-Training-Simulation”云桌面正在运行，其配置为Linux Ubuntu22.04 + IsaacSim4.5 + IsaacLab2.1.0（Luna二开专用），计算费用为8.15 CNY/hr，存储费用为0.05 CNY/hr。界面右下角有“+ Create”按钮，下方有“Running”状态标识，中间有一个蓝色的链接图标，箭头指向该图标，提示点击链接可进行相关操作。](data:image/jpeg;base64,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1. Login to use

![图片展示的是Luna SDK开发指南中Cloud Desktop创建流程中登录界面。画面中显示“Welcome to Ubuntu 20.04.5 LTS”字样，背景为紫色几何图案。画面右上角有“52 MB”标识，下方弹出“Connect Your Online Accounts”窗口，提示可连接Google、GitHub、Microsoft等账号。该图片对应文档中“Cloud Desktop Creation”步骤里“Login to use”环节，直观呈现了登录界面样式。](data:image/jpeg;base64,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EZR13nYic6Zvn56JP5sReZ8tgIvM1V76eGFpnwxaImJknWbfRmJSZ1vVM20gFnPKJ+lGyTpPhp7LERFUTVej4rE2mm0x4Ym+cGxL2qmaY6e8oi01TH50zv0sWneY8M526LVERePoxFM3iZ3TyqXmb+Gbzb9ZaoiYi9MVRlab7kzFUxE575zJFHj8MxFvpXyS2QPoUxVa+U3m6xR9KabTMTnEt9OBrOJN4n3y3U05WpmfC458aTwNOHgXqtiafVj7m7Doppo+jlDL82LDzZcTKm1i20WSNFujn58gCqhCgAAAAKKgmxRIVAAQBYAQnRQXRAWUCDcJADQAgURUUAAAABQsLuBpB1Larv1QNgg+AKABOYd1RQNUgFPMgkDdTcFDYEBUUUCDsBuuyAKAgeQKKAAAAKioAAooIEBCgizokLApdfgm5pILa8SfA+JogR8FSIXLcFjc0LZG0oET5LF9zYsBAoKiooACKAoACAAKoAAKKiggAoIoAKACwiooAAqKAAgKigQAiikAACAuwCqAgAAoCAEAoqKAAiqAAAgACiovYBY8k81QPiABsqaQqBsdQADcAAQABQAEJMxAn7z+JJIJtGeZtAAk6B7Dv0ATbIJRBABj3N8l76IDFJjpLJjMWyETLok9dVnTpNmPt7ARqw3ZJuM6SYYyyqYzoGmFWqVaLKToIwqYyzq/NYyIwYVNk7sJtYRhYUB8qA+s/AAAAAAAAADyuY/pM9oeq8vmP6TPaGsPL0cr87lBXR9BFAUNQAM+pkAKiwoa6mka2LG26BO9tCdTyubAe371+4+Jooed8zSZ8zPSDTQDfrCx7DznLYvvAKAKAAAAWvMOqItTZowovU6N1ajFYRYgaZRSWWAIRN1SNV1FZRG6kaAICwqlljIhUUICAUCwMo0WEjRYBQFQAFFsigRCoooAgKCqZ+07igBbPzAXpAXBYLARAqgQCKAFmUaIoAAAADs4Ou8eGXGywq5oqureFenERnCRE+SUTE0RVdlac8oHbaRHWJW0FN7az2WctQTTRd7zqGwhFzM1S3nIsUteBRSIsAAAoLZN1AsfAAP50PebkiLP3JtmbrAE9z3hqBGn3FtDQFI2seawCJAsaojSmwgCxqEagufVS8FwSYuRFp3W5cALwAbpN73iVibkgwxcOnEptMZ9XBi4NWHPWHorMRVTaqBi47eUmfR043DzTEzGjmi+Y52aUBEAAU1sW6AHQ3AAVAI81C4AACooAAAAAKCbKAAaABmEaCgqApsRnJGgAEZgt0U1UCQAVFBFAEUAABQAAAAABYSFAAAJuAAKAAAAAAAAKAbgpqAGwALskKbgli1lsIBbqWFCeqot0AAEhQA2AAJADQFAQgAUADU7gAAAAFjO6p3BRN1sBsGgAXO4ABYDuKAigAAKAAAAAAAAAAAAAoIAAqAKACCgCKAAAACgAAAAAAAC2RQSdQnU2AAASYupoTtTbXMWGcxfVhMWdpltqG5t7jeDb2Q0pteY12AnOURhi4VNcWqhx42DVRPWHfO/bQtkJZt5ff3o7Mbhoqzoyno5aqZpm1UTAxZpj7FTZdhA9qfcsaAtNc0TembT8XocNjxiU+GubVPOkpvE3v8ASZsV7N87TqR5S5eH4mK48FeVXV1w5eFZ4WJVhVROHNpejh8ww7R6y8T5ZvLmE03n2G109qnjcCr9aY7tkcTgTpiQ8Gc9c0iOkRBs0+ijEonSqJ9rKJp6vnJmfP3rE+c+82afR5EaPA9fixpiSscTjftKo7Su009/Y9kPCji8eP8A6lU95ZRx2PEfnLs09vpYvLxfn+N1j3FfH480zaqmJ7GzT2pnWdDTo+Uxub8fgVWqqo8p8LX+XeMjPxUfZXTL6/QfIfl3jJ/Wo+ywr55x95mK6LW+qsx2bfY1RExaYyc2JgzT+Zfw99HyU894/fEp9zGed8fOuNk37um4+pi17xaFh8j+VuMqqvOJ7bNsc642mLRVTV3Pdm31Ns9DtD5qnn3E/rU0T7Wynn1cZVYNM9pS4UlfQ7+Z73hU8/i2eBbs2U8+wY1orhOirt7KxnNrw8mnnnCz+dTWyjnnCT4c649idNHp7z1Ijrr0ceDzHh8evw4dc3b/AJxhzOdWiWaG2PzrkWy1yaox8PrC+vo+sitkdjK+eW7XOJTfWdJIxKYm+egNmWecGfwYetp8/cnrY6dPiI2ZyWnq1+tjpKTixbKAbr6pDT66fqwetmdrA3ZxqnZpnFqlPWVA6M0m0NPrJ6sJqmZ1B1TMWzskzT5OaZmdUy8wdPrKepOLF5/BzLE7XkG2cSI0zPXTbSGq/mXQZetq2Sa5mc5YgF5L9A94Ee16PBc0xMCYpxJ8eHpnrDz+ifco+w4ficLiKIqwq7xvG7d+L4zCxa8KuKsOqaao3iXtcDziKpijiYiJ+tGi7TT2Y2vMp9yYddNdMVUTE0zv5KqEZ/gHY8wNvIFkE2PwXZOwHwVDe4MaqKapzpj2tc8PRVPTfJuAc1XCzMTaq8znnDVVw9cfqx7Ju7ickHicdTXeKbZ6ub5viTF7W7vR4irxY1dV7xfKerDTWRXLHCzfOr3NlPD0xq3R57pt23BjGHRE/mxLO20RYjy96bZfeKvnEnmW6ymt5t7gXfVPO1l32zSdItt1BbZ6R1TbXTcnfX2LPXUD9bzlNIzm28rneUi22gLndNL3vY2tO+sL7QJ9mUamuucdEqmKPpVTDnxOLopv4c6vIHTneemzCuuiiL1VWcGJxVdcWibQ0TMzN5zlNrp3YnGRn6uJmfPRy4mPiYn502jyau4ge47kKBpLt5dpiexxPR5fERheK+UysSseb8JHG8HXhWtMxeJjq/O8SirDrmjFj6dOUv0+M9dc3yXpby/1eLTxWHH0Z+jVbr1dcLUebyzF+jOHXPaXbE3nN4WHVNFcVRL2sLFpxaKbTF3pldMMttk6ZzPYteO2Rb6VonLqTe8azdWyYIyvfXoTErebRE7az7QLTeexpVppt7CNdNOsLERla9o3A631y0La3zm6Wyi0+y+xradIneUF3mLXvPvJm14n+ZL5xOk7XY11xRRM7X9gGLiRgx4qpi8ZQ8fiMacSuZnKnptDLieIqxq5z+jtDTnef4aPPnnvs4Z5b7RMpvPVZ20Sd/fmt+kZdHNhJtG2XdZjO0z7yPboRplHmBfK/TI8ti2czeDWM57im2c3ndc7zMXt8EjPrESsxeM87bA7uHxPFTF/zo1u2xE2m0bZvOwq5w6rxPlL0Yq8URVM3jpfN6eHluarthluFovEzFqZ9qzNpzzpnOYjQtr4c8s7xoRMxlTnGsxMOjZeLRGcxb3Sttv1dpnJNppmb20m+RNukXnPLZBJvFNotc3ynXWbLH59U/Rve0RSR4cozmYUOkzMzG91mPFNrRM1aJnppHTq2UYVWJNNspjdm2RY12mbzMRerzZ001VVWiJ8ob8PAptF4+lu3RTacpnJ58+PrwNNGDlaqqqqrppZtpoimIiNpus3mbxlLJwyzuQlovfdZlBjaLOaAC2LEKCWUAAAABQBAsWUZAAAsLGgAAAAoQKAAACigCAEAAACosX2FRdczvKgn3rYJ2QL55llyMo0BP5spqWQVIUFALAZrmWNxQkVBFAUAAIUAAyQNjYBT+IoABuAqKAAgFslBQCEBQ3FFzIy1BEWA7XRV3N9SwBovvDaECM1OoACipsoAAIAKKAIAAoqLAGwAKAikAAoAAKAqAqwbggAAoCACgAICpCigCBF1CAFRUUsAAqKgACiggAWAVFFAEAAUBQD4AgLuR5gB3LKgAAaBodQNg3VFQAAAABBDupcE8joGdgM/ak9IWYTac8gO6brPeU6gTlCSs6IgJkSdxElOy9UnuCJPZUkGNpta6THW+iza+eaaIibsZhlEsZVEnNjMMmMhWNWyVRaFlJvbMZYVTsxllNpjzYAxnowm0Q2TGbXVAlLiAj5UB9Z+AAAAAAAAAHl8w/SZ7Q9R5fMf0me0NYeXo5X53MIro+gAb2FAANtzzI9wCx2NU3WALZmRJrYFNrIsAbFveWPjdQ6yaST3W2aCQsdJCPuUXQO52FAANDqJOwN+BGV21hhxamzNWoxZR+atgaKdFSFAZUbpDOIsKAAiwWWFUhQRQghlMWBI1ZsI1ZpQIFUAFQAFFRUFAVQUQAFUWIDYDb4rHlomWuXmsZwB98wsxfsZlukoLYjQ9upYUztkttYnRInqagobKAbpbLRVUAAABSUUV1cHifq1Op5lN6aol6OFV46YlY643cZpEXnOTWdDLcaXVYi3ZhETDKNMxpZ8tE3XoKhHUjQO4HuI8vetuqSCx1SylswPuOpoAaz5ikdAQVBRadSdFhEXuk+SsdxYvcAUBlaAY+863yWfLY0EJ3T4hl7AMrZ37rbM75dSPeoa9TXzI13L280EnJbxvY33NPMU2zKbrOoBFtllIyAAASrObTo5sfAifpUbbOomPeM2beVVfxWmLD0MfAium8auGumaJtVkOdx0xFjMRkAAAAAAFgBQAAAAgANhQQVAWwAAZgoC7ZAWJyPibgRkb5ELCiKdjYA3NgCVRQAAAAAAABQAAFACCEABQAABQEUAAFAAAWMwQFBFhFACDcANdiJBUiFOoHYDdA8rBuACgBAAAdgDUAAAUAARQANgANgAAFToAuYmigHYO4EgAaCoAoAigAAKAAEAAAAAAAAAAACiAAoAIoAAAAobgIASB5gCgAB3AQN1ugoGWSggTCggtiQQAFgkgkES3VQWNcjZMRLCY8nXHNUI6g2pnrBkEX3AYYmHTXE3hmsRle+4PPxMGaJvGcNU65vVnwzE93PjcNFWdIxY4hcSJoqtMSgmiFSFRmp4ppqvGrr4Xipj6OJ73LYn6WU6JZs29enrGd2W7z+H4maLU13t1d9M01Rembx1crjpqUARQAAAAAAmL6CgwxaKMWLVQ8riOGqwqpmM6ZevLGYiqnwznHRqU08MdnFcHNETXh6dHHE379G5WLGFVMTE9WqaZh0WSYvq6TLSNA3YeFTVXaa4p9jpjl14vTixMT0i7puUk24Lq755dMa4k/Ya55fX+0j3LpbhY450kq2dc8uxrZZwxngcfek0nTXNZLOmeDxo/VljPC48fqSnc1WGBiTg4lNdM6Tm+hw8SnFoiumddXg/NsaYv6qqYnpDv5Z67Cvh4uHVTTrEzFnPiYbjUleisxvEpsPLqzy0tNVXVnGNMaxeGtYlRupxqZ1yZ+KJ0lzZEZaCadcEueMSacmcY0bwppsEiqmd1E0AAdzMNr5gSdtRQT7hU8viBtnqqb+Rt5gbntO4AT5qgFj4h5WA9gXubg6OF4zG4ar/Z1zEdJ0l7nB81wcePDXMYdekROj5v8Amy5rsfa+cI+Y4PmOPw8xHi8eH9WXt8HzDA4m0RV4K/qyu007c87iHVUBQED2FwNhQEY41XgoqnXVl/3c3HVWopo3uDi9h7M56GdrT74N0Uk80iMstFuBPWBGXQE/iWtkWy1Jm4BqJppMSCzobEzaLxMTHVpr4jDojW89DZptvKzMRrMRDir4yf1aXLViVVZTVMwLHo18Th0ecuavjK84pyid3JETbyL5oMqqq6oma58TEEAAAFgEBYFSfuevwlFsCi2eV3kxETMd3s4dFsOI2i0QsKymc72jrZo4vh6OK4avBxIvTVFm/LKdL55dC9/zpymYlpl+ecXyzieHxK49XNXhnWIu45iqirSaZh+icZhxP09pylxYnD4eJE+PDpmNc2/eeq6lfGYfE4tH5tfvdFHMK4iPFTez3cXk/C13+j4J/wDLk4cbkNUf2OJfa0w3OJF1lPFaKONwZn6U263b6MbDqzpqiYjKzhxuU8VhxnR4o2s5K8PEwavp01UTveG5nteqzzHu3zyt1M8s9Xh0cRi0VXiubx1dGHzDEtMVRFU9WupZnHqRlV/BIzmI3mLOTD47Dm15t30b6eIwqqZmMSJiMs5zg21uVnVXFFPiqmPDGcS8risecaqYibU+TLi+JnFq8NEz4I2cs+27jnnvtHLPPfaHZct9L+4vO83zuReJyvk5OafhovsgtnaJ9pf3306gQZbm/f7iJvOU3AnSNOi265RqRl262NIvsKk2tM/caTl0Ot5XP8I2kFzvvbWXRwtdvoTrrDm01Im2k5rjbLuLLq7epe9pqz621Jzi+cxa1+kteBiRXTe9onKbNmVombabPXLubj0Lacqarz4b3joR+dabTMZRMzkUxE1REfSi9sspltowa8ormIiM7az7mcspj5VqziKZtfPKzZGFXVTM5eGZdFGHGHpFpZ00uGXG9Ea8PBpom9Oc+bZadcoXcee5XLyGmYs5ogAqCCyQCKCAoAIoAAACikdgECMg3AFRQNSAFJVADyBUAAAFFAEAAAAUAAWNTK5HUD2L3JzXdBIv5XOmix1ASyl9wU2VFQD2BFgI+9QgUDZUEICRVAAFIBFBAID4iqAAAAoIAAAKKHctmQgEFlA3zVIzMhVzMgQIWE26LsAtvakbwu2YHmR3UQJVFBItJCgoAgAooAAAgACqWIIAUEUABQIAVNFAAFURUAABQQAAFCyAAKpYECyh2A7h3XRFAAAEBQAAsKoCAqKKAIAAoCwCLYED2r2RQIA2AU7GiB3NiD4AbhIKKggAAAIAEgAbgh3VJAmck3UtkCJsvRJnLJA8kXQ3BjKL1QESWXtSctQQkEGNWjGrZnMMJGWMoztDGQYsZtdnZjMZjNY901uqbCNd/wDzMatmydGE6Axq1YTmynVjKoxFv/5QHyYD6z+fgAAAAAAADy+YfpM9oeo8vmH6TPaGsfL0cr87mAdH0Q3AA22FBP4ikKH3gRqgR7Ty0PisgJOll63NNdVDcj79D+bGgLui7+ZlsBt3Dddvagsp0CY0lVBZm8oAtOdUI2YMXkG61pLqllajIAaIVIUFhmwhlIq3LoKqrCLCCgCkMtUWkCzIEFgIGkABQFgCwCCwCiooAHxN1VQ1Ns1A38ljvmnVYi8Zgdd1jTLMmRFNzfyXUi+4GUh2IvuCibKoACgKBYsoNJYUA2dHCYtq5pnJz7rF4mJjYJ2enF7FonVhgV+OmJ3bGo7TuAm40X1U2NBDQF8gDUjU3A6GwvUEVNt13A2+K2S34ZLGsgTokRdZ0I0Am9tD2Ge0me6LouigoBYBkxZAk6p03WS+ukAfHU3nS5JnYQi8RFje+vYjTT3ruqhnuRr5ke9A/iTpnJ1z9oBoFvMAAAAAAAY4mFTiU/SjPqyXMSzfl52JhThzN/zWuM+z1KoiqLVReHFj8PNFV6c6fIc7i0CojAAAtkWAFAAAAAAjMABTcEupBsAAC90LqKm6m4B2AA+C2uEqIuoAAoAAAAAAAECgAEBCgAAAAAAAAqKAACgAAAALsAbB5ABYAzI8xQTYUnQEU9oAbi9kEhQsB0AuAAAAACgIAKAAGgAGRABE5GQAd1jQnqCQoWBO6gAQZgAAKAKigIigAAKAAAAAAAAAoICgiooAICooAigIoAAAih5gB3AAAALAACkzddNTe+SCAbAGyoooSAJYsoBAAJYsoBEdUmFJDbXVCaQ2zF4YVQ645erTHuahOUtqGnvOnsJmQXKYSyxnpADGuiKotaLOPF4eabzRnHR3bJaRNPL0nPKVmbau/Fwaao0tPVx4mDVhzec4GbGFyc4RYGLDO/k3YGPVhTbWno0jNmx6+HXTiU3om7Ls8jCxasKfFTOXR6eBjU41MTGvRzuNjUrMVGVAAAAAACwAW9zi4vhIq+lhZTvHV2nZZUrwZiYq8NWUpfO0PX4jhoxb+CLVvMxcOrCqmK49rcrNjG82tLPCxq8OdZmGtJno3jdeElsenh8XRVFqtW2KoqjKp49Pmyprrpn6MunvL9XSZ+r16c9vaWmNPucFHF4kWiqMnRTxOHVEZzTLpM411St8TG8yszePbZjTVFUfRqiTbTdqWVqSLaM16dSN+5Pey9JqMoqtqsVxLD2XSznlwsalm2662yaqarMoru82XCv0Z0yDLqZWc7LPIAJtDPZlFdUbsQG2Ma2sXZxiRLnkiBHVFUTpMK5bZrTXVGkqadSNMYsxrF2cYsTrkGmewkVROkxdfvELeR7zsfwAAAt5B8S4BuqAfA2/AUBI89CLmnYDzssZTfNPNQd/B80xsCYiufHR0nV7XC8fgcRGVUU1fVl8rdYmYzjLzXY+13NtHzPCc0x8G0VT6yjpL2uF5jgcRERFXhq+rUqadZ0BUF3Qj+IHuefxdc1Y0xG2XZ3YlUUYc1Ts8u8zN5nOc5FhNs8+9yd9Z3M+hnNr5IpOplJ7jMNJLLdjMxETebQ1V8Vh0TlN+wNtOemazFuke1wV8bX4bURZzVYmJXN5qB6VfEYdGtWbnxOMn/6cRT3cd77zC2iNgZ14tdU51e5r3vusxZGVDawASKKiAICoAMrWSAEFkFZ4NPixqY87vY0iMp0eZwNPix48ou9TTS8Tk1EqRERM2zjS6zP0pi+u+qWta+mmW5VpbpEx36gk0xVRMTF4taXn4lHgrmJjKHpbzNtJ20c/F4fiw/FETl7CkccWyv7SxGsX95EZRaL6sqkxe19JmM5Y14WHXExVTFpZ/wA5kTaMvf7TdV5+NyrhcXOaIpnrDix+Q0zng1zTHnm92+m0EbX90NTOw8+XyeNyficOJmIiqPJ5vFYONhzMV4VdEdZffWytO7GrDpq/Oppn2Lc7Zpm4yvzqKpjOJZ04tXW77bH5VwmNEzVhU3zvLz+I9HMKb+qxKqZ89GfyY91Z4r5311OU2y3ZRiUTMZ+934/o/wAVRecOaa49zz8XguJwf7TCqt1tkbrOsp5jPWMpibsuzjvNNW8Sypxaut16jqdMX10XpH8w1U4k1TH0Lz5OjDwsSv8AUqiJ6wbjU7+GE22ifwJ65ZOingsarOKPvyb6eXVzMXqiPKTca6a4PdaDtm9SjltOtVc+LybqOAwYj6UX/gnVF6K8b7vKVimqr82Jnd7lHDYdMfRoiJjrm2xRTExMUxHZnqa928bhsLFprtNExEvSw8C8XriJytaPjd0wLOLlJqNyaY00U06RHhtZlF95vIMW7XZHmAgAKACAt0AUIUABAAAAAOpqCgoAWNxAUOwBYIFBUAUN0DcABQFDsCAAAAKAtgM7G0C31kC0+RroeUL0QI1kO5uB3M7kKKihugbmnmQbAKAoAgthFFANgANwXRFAANUVQAAABQABAUQVSCBA7KAItwgDddQhFDey6GwG6wRonaQW14NzZYyyQLHcNgVFBQAAFRQAABAFBQgAAVAAFFACVQBQBRQQNQABRANgAIIXcDoEaCKKFgFRUAFAkBFAEBQAAFFRUAI0BVRQABAAFFRQDoKgBB3AFEAACQBQXYQIBABUAAQDIAOwbAJcCwCaLKSghlupPnoCTFwJBiioBkncEEABJY7skGUtZhLO92E6iIkyqSDGc4yhht5s9NGOWoaYzp5sdmU5fS6sMxljOrGYZzDCREz6igPkQH138/AAAAAAAAHl8x/SZ7Q9R5fMP0me0NY+Xo5X53MBLo+idyPLUAX4iLboAEQAdwgUXQOggQW6nmTCgtjSfaR0lAI/6EZmuihpqu6KigChEXWyQtwS15b8Km0XaI1ydNOVMQqyM9xIlRqCwWBVhWKwLGcaJKwkgAsQqiwKgAtMXFFpQuDMIWxoIAVAAUWAAARVhUAUIIVVO4AfAW2SxqBboffJ22VFTut4NIXUEhYggABQSNFBVAUEWAFUAUAQCAgG7hsSaarS7ukvMd3D4nrKLTObUreDcArqLGqRqoiRkp3PeBYNwBfiAFpOtwA7rCZrewLOaX2Iva5l7UXQBAoMrQWgEi/TIi18lsRfcADXO+QCdOha+agmnWVnWC+VzXyAsRrkEXy2A3TXJlGqaa/cBYnZU31BUNQAAAWxYEFsWBFgsoaEnTNQNOXiOHvHipckxMTnq9VoxsCmu80x9Ic8sXAM66fDNpizHTzRz8KAAAAAAAACgiwAEZamwCiooCKAaFvMgBfakC6qJooABCgllRQAAAAABQgNwLAoAAFwAAEABQVFARQAAUAABbe4EFjUAAAuXDSQIWNCBBOy7EAAfAAVFAAALAAAAAAqKAJstwQUAAANBZBN1sG4EBsQAQAAKCKgCm4AigAAAAKAAAAEAAAAAAoACKCKAAAAAAAAeQAAAe0BQARf4ILsKljsKBqh7DcAXSCcwSy+020NvMDJFkAgAAAAAAAAAAmLgLth4Ut1bEmLw6Y56mllYJK6ZJ1dJ3VY1NZ00/7pv7FvldQvuTHXM9xsgbZwlURVGi9CMrqjnxeGpqi9LlqpmmZvEvSY10+Oc0ZuLzItdXTi8NrNMuaYmMpp9ppnpRnh11UVXpm1mMaXS90s2mrHpcPxNOLTarKW63th5ETMTk7eG4qJ+hXlPVjLD0a26xYz006o53sACbUAUAAAAitWLg04kTFUZ7NhOeqy6LHkcRgVYNU2i8S59Js96aYqyqjKXn8XwfgqmqjTo3MmbHEJe0569Fb8sCTbdYEaKaqqfzZlvw+Krpi0w0XF6rPBMq78Pi6Ji1V4lvpxKZjKY9ryS87TLc4l+rXW9iM9zd5dGNXR+tLfRxkxP06HT3kbxy27YLNNPE4c6zm3U1xOkw3LK1uETMQzipiX8mcsMamm2KsjOWqImNZXx7OGXAs7xLi2CRVksONxsZoojIyTcgkCTZQEhYqmNJST4gzjEqjzZetvrDV3MokG+MWmWUTF4zcyqmnT8By3m+rP1lV9Q032zPY0+tneIZRix0BsNMmuMandlGLTM6hpkJFUTGsLeOsAWJImNlEQLHQD4kTbOJVNwd3Ccy4jAtHi8dHSp7HC80wMbKufV1dKvxfMkeS7H2tMxMXjOOo+S4fjMfh5vh4k+HpOj1+G51h12p4iPBPWM4U16O3jqrYcUxOdU/c4ptOsZLx3F4U1xPrKfDbKYm7ir46nPwRE91NOze+jGqqmn86YjvNnnYnF4te/h8ohpmZnWZnui6ehicZh038MTMuerja5/Njww57XJmyaqrXXVXN5mWKx2PYJUFIgRGST7E01kFlC9xAABYJBRBbFkVBbERn5Agy9iWAglQHZy2mPpzo7o2zzmzl5fFsDxXzmXXnfWc/fZqJfJOdp89OqZWW0zOkROca6SmsTMRby8wXS8xFpicrkxlaNomIM5n6W2RnFr2y2kHBjYfgrmI/MnRqztGkb9HfjUePDtvEZTDhtaIj7kqnTS9kjW/WVym1r9eybSikb3lfbuZbRpmaaf9gTLy/BdbQmm3/ZY2+PRAzt189C3a+htfbok5ecguumXkk0U1RaYvHWy9bTvrY3tEa31DblxuX8NjZV4VMxOmTR+R+Epm9GHFM65Q9GNb6n5sb3su1efPL6KY/2dNFuzCrh66LfQl6k3tM2vaTXKEXbyJiYmLxaUetVTTV+dETm11cNhzGlvOE0becjsq4P6tfvaq+GxKdontKaNtJKzRVT+dEx3hJRQAAAAJyi85QUzFUXiYsqgZ7xYTYLAAoAAAACAAAAKqbqABuIBsWUALAoACgIAApuCgigBsAgAoqCgEanctuuwGkaEb7G2mZkgdy11NwICCBTZQhAIADZQFOgRqAKQCgCAKAmSwAACKqKgKBAAKAAgKgKodgABBTZFAt5r7EUUhY84SF9iBOiwkZ3yXMAtcjLUyhBQ8yAFAUAAARRUUABABYFAACBbIAAoCgAoAACgigAAKAAgE6igAIoKAKggoQAbqCKSEACggAAKCKACgKAAgACgALAL8UEUAF+KKgQAACiiKIECKAACKeYgmwu6ACgIBoAIICTsvtO4JZJjKVhJ0gEWdCxMAxM/YaIglRopMAkosoDGrRP1WVUZMRNJSx3ZaMZE0lSWyUEYVMWc5sZjLQGMsM7yzljVlPcZYZ2YS21ZZT3a9wQWwI+QAfXfz8AAAAAAAAeXzD9IntD1Hl8w/SZ7Q1h5enlfncxcgh0fQCxH82IAVF+8A3ADyD4KBsRH3G52UC2UaEamYqkewjW5pGWwh8Fj4J8FQTSyhHUUF7p2UIWxC7CfUw6by6bNeBG7bCtxIiygNKXzEnUVlDKJsxhRWSSsaJIgyjJjCqrIBAWMkhRVsWWNFQIVFaAAQAFWAgAWyMkVFABUXdVF3TNYi/YDz+5Yy01T71i1tfaBEZT1W+hlciLX80U387KkFosChBAEeagoACgACwECqAKEAgWUFSrDPBqmiu+zWXmZFl09SMyzRwmJ4oz1dEatO6WU3I6gKmsXWwAG+YEm9tSPM2FIXbU3ACIiRYAiJhPDn5MhFSxEWUAAuCWzUAEnLTRSPMEyyPxUyULFtOpl71QTXQ3O+hpHYCN+igBfOyaKdwLZou4AWIUAAUAAAAAAIym8AJrbXiYdNcZxm4sXDnDnPR6LGqIqyrjJGcsHmjfj4E050aNGo5WaABAABUAURQDcIAFQUX4J7FACAAFURTyAOoKCRN1AAAAAAAUAAFAAEA3AAAABRRFAAAAFAAAAFRQI1Aj7gDYiczcBTc2QNi+pAoKioJuqKAAAAARnAAAACoAoAIqApAAZGpqRYAUADQA3AABQRRBVQBBQAAFAAAAAAAABYAQABQAABFAAACAAABQADcAAAAMjYBb2LgGybC2BAUDyOuREZGoHYN7HkBIbgGgX6AAAAAAAAAAAAAAAsSYuwmNYlsSbNY5LGCTO1ltbRHaXalulljToRtbzNYgA6nkKF7mc2tokaRbS8fBY26WQLMa8Omqm0wyzv5KGnFi8NNOdDnqvH50WepfLNrxMKjEpzjMZsefa8apGtp16ujE4aY00aJiYvfJKy6MDiKqZ8Fc3pd9NUVRFpvDx927BxasOdb0sZY9h6dxhhY1OLGTaxpWICAAAAEABoLLAJ5cnFcHTiTNVFoqebXRVh1Wri3m91pxsGnFifFHZqZJ0vGjO5te7djcPXgzpeGmezpGKAKgACHdRKJZlFVUaVSgbput1HE1073bqeNtP06Zca5TrN1xysa6no08Vh1b2bYqoqjKYu8iZjSyxMxpVMNzitTN7EaZSR4onN5dGPiUaVXbaOMq/Xi7XXhfK9celFXVnFp0lwU8XRMdIbaeIw50rYvCxy8G9urbIa4xIzzu2RMOOXDyxNG5IrCJ0VFASI6mYBOmSooJ8CAAgI0ACdMlSQLFw6Aty89ZSwC+KY3Xx1dWMncFmuqcrnjqjWcmMzFMebXVVeZ1dcOHclk2zrxauurGa6pvnNmOe1+5N/FH3PVjhMZ2akZRVVvVPtY3vM/iZRqkRN4a0rKaptrPeF8VUb5MbWvle2Zf6XcGU11xEZ6+a+trvlVrowmLaTf4pa0Tl96aiNsY1f1pKeIxI0n3tV9VtN8k6IvZu+dYmmUr85rzaYpmrRnGHMWS4Y/VLNs44qpl88q6MPU0+K8s4opp0iJ7nu8E6WXzqq35l2dOPVNvFTa7XVamYifL4MJrtfeYYyxwh0umMaJvemV9fTZyTVVN7pGThllPETTr9fSy9dR1cV/JbucNOz11HVYxaJnVxX8y/mbTTu8dP1oXx0fWhwZdS8dU2O+8TnEwt/OHn+9YmYnKZNjv8SuDxVfWPFV9aTY7jNwxXVG8r6yrrJsfR8JT4cCns205RTeNIeFgcxxsOPDNqqbWtLvweZ4Vf9peiWuqJp32i8aT/HzIvaIjp72vDxKK6YmmunTaWy8R4YytreOjSaLZ2ifLv5m0zETN1tnPsjsn6298pyAmc5mJvl01cXFYcU13jO7tptaJ6Z/gwrp8dFp6ZB4edl4s9tjreVqpmKpvGca3Ndfcy0d7xvFzt7bm0/fmX0z9oETM+3Utv5Gusf8AQ265e1AqjMm+/cmdJOnS15AyiLZXtbdZtebR1SemWlljXLPQGOuUe9lEzM7JGfbyZYVFVcz6uPFVe1oBIt/N075RrNnZh8BjVzF4imI6y6MPlm+JifZXVNx5kafwWmJqn6MTeNoh7WHwWDR+reest9NFFOlMRMeR0p1PEw+Fxq86aJ9uToo5bXNvFVTT5PWtnN4IvN7ZTHU1E3XDRy3Bi3jma/KXm895fTh0U42BR4aYyqiPi+gy00Y4lFOLh1UVRemq8LZPBLZ3fC7GujDmU4nCcViYM028M5TPRjRxERhRMznbZmYusb/C1YuNRhxlPino5cbiaq5tTlDRs1MYM8XGqxJzyjpCUV1UT9GcmBGsNXQ7sLiIryqyl0RnGTycpmdm7BxqsOdbwxZsegrVh40YnSGxzqqAAAAQCACigAAAG6oIKEAoLmgCgAQCBsCiooAAIAAoAAuxl5kdAIi1iNfJdsjugRouZOwACigCB3LBAKZJsooqEAL2AUAQAO4KBuBALuigABuAALAIoIFgBRQABfggAdQLLGuQQKbqkHW6CkC7gkaLMG+RsBaykqgIKKAAAIAoKiggCgqKAACAoChAoAACwQAG4qKAAAAoCAQL8ARQRQAFCBAWCAAFRQABUVAAAAFUBFURQAEAAAFFAEAhSdwNixuIGyooAKAAigAAAACAAAAACAC7dEny0AlFEE1gmPaAISdiUESVQEsjJI1BJyFvdjIEosoCTF0mLMkqBgkwoqMJyLlRsiVjLGdN2TGRGM6wk2mM50WdJnolp8hlhPe7HSWUxZjIIAD5AB9d/PgAAAAAAAB5fMP0me0PUeXzD9JntDWHl6eV+dzd9AV0fQOxGnmAB03NvIA+46djM7goe0UA3/6LvPvQOobCgTpPkdzcUm6ooGeh/NiT+YQGUaMWUaKFVt011WYidSmnxVWkI34cWoZsadLMlbgELYUFsWFZxoJEqAAALBYVVpRaQWUWUCMo0WEjRYSKoDSAAoqKUAWEEZIooACmiLsqm62I1yPMFiN/uL5Znnnkt/einRU2zOgLmBAG6ooJCgqgAKIoAZECqAigAKB7VAAGzCq8GJE7PQiYqi8PN1h1cJiT+bOixrDLXZ0xC7m+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Q2AACQU0J8gsIvdC5uKHYBCJC2epsC75ISagEGxfQDYACM9AkgAuSd9ANwJ0AD2gAHcAJAAAABQAAjQBAgtkaALdF3FQLqCLJIBkmygiKgKsh3ACPMI1QDcMgBUkDUVAVFANgAABQ1kAAEAIAXsR1CwAQT2ADQAAFUnolxBZ0CwAAAAKu4iwgBYAAFUsbAAACoAAbIKAAAKAAAIAApCzofEj7wJ7rsigWWE7KgCQoALugSEaAC9hPaKKdwABFAAF1DYAAAUsBIGyKaEC+YJApPQDSwGyBsbEqBCKXFAJQXdFyJAsaHRQNgXZBLqllAAQFRRQIykgBSfMA3BYRQAAABUVAAFAAAEVbAbgEkLYEUEUFNgAIAABTbMjQFFBALAAACgIAAAogdwBRQA1CFQIAAU2EUAQAAF2AAIBRQQIAFFAABAAFBTYBUVAAAAQAAFBA3AFBQABABRQAAAAURQAANdF31A6nnYvJ+KC5XOhqAKHRAAAABRFQAAAVFAAAAAAAEAAABAAAAFAEAADUDcDqBOoEhqIIRqEgFg8wLeZJB5gdU3WUQI+5OygJvY7B8QQD2gIogkh/ABJTfPVZse0EOuRonkBOeqRqttUuCGnkvf3pt5oJOqfFdcj4AlvwRZ2SY2ESUUBO02TsuUoAMZvfcB+fAP0L+bAAAAAAAAL0cXF/wBq7eji4r+1js1g9PKfM0qbpOrq+kpGc2Rswqb5hI3xFohUvlZVdZ2WnRUp0VECwosIUBVAAAUFRQAAVUUUBQAUCF7G+hGgqkx7wBQBRUUAAVQAAUUABQFD7lTzUBY0TL2ltIBdNF6JutugCou4oqALncLAChsKKigARGYBtooKAqiL7DbIkBTYAAUUBAAFAUAO4AqAL3M/Ye1YFRd9U2yXuIkfctjJY6ipGi+8L+6AIPaWAJ18lNtT/uAewiei559ASL+5e5r/ANUBYjI8j2bk5xNtAN8jY6HXMF3z2Lbe4/nI28gOgdr2X2gmXtU9tifLQU3y0O2xOnkZXA8l6yEgb5bhrqWA3J8zWM4hQT2KSIAACoA7+Er8WHETrDe87Armiu+z0ImKoiYald8LuKA00IoKXAjUQ1kIXbqCKiimwTFwDU+AAAAfEtAsxkCKmaoBJnIAbBsB7NCPI7AEGypIBnbzVNwILGygaaJuoCRmoAaaJv8AxFiIsB7C4AagWt2AI0DUAsRoAeaoAGQAb3FsAkmp30UE2BQN01AA+IoJMEXVAFEAFgBIIzFBPibFpMwPYdzcsAElgDO+QWATVQD4HY7G4JEKQAnZTQ+AGfRLZZL5nsBOoHcAglQI0VIVBJ0Y2ZiiRoVaKAwWYvtZkFqNVeHFcZxm4sbBmibxo9CZzYzETH0oTRlHmDfxHDzTPiozaO6WOOtACAAAAAAAAAKgAACooIuwACACwAAAoAAAAB2AgAAAAAAAAAAACcg2ADXQANToud0A3XrZABe5sXyBOyodwMxTK4ibLc6WQUM7k9JBDdUWwJPnquyEir8E3FgCyAC7+aL8DMEPau90ELmh5GgHkqQSBsZAKWCPMEF2zJQUF+CSISHmsipoGmp3EAANy0m+YCoWAOnUCwFy4aTkKAX94gbAKAASG6wISgop5SG4AIoG594dgDY7gGxqamwCpqWQA6gAL30AA1AAANdQAuB7BV8pQ3EC/UXsAX94hsC75Zm4bgdiPIBQADZU3zVBFLHxBN1O4ALGoKi6B5oAEAAALsRqCmwEeYAdhABQAQFAFAAAAAO6KuwizHkBrseSxoRAJsyPYmSCgAbBbKOgAusAgAQKoGgG2YQCgQtkACwAAFgUAgNkUAAUgjMD4AboBZdzcUDYjzAOy3EDRNe6keQAd1ANywgeSkG4ACACioseYAbqAEqm5uiqAAAAqKgACgAACKseaCgEAApBCAAKu5uAAAKG4KbkEfcqAAAAAoIAACggACigABALAQIAoigAACCgABAAp5CKACiooACAAKLAAAICggAAAAKioBsQCiosAAALCQqKAAAAAoACKAXzBbZHwImdSJ2QLLJ8SwBAWQUAAAFRRAAACBFUAAAAAABAAAAAAQABQAABAAAAkDcCUCT2HxLAeaL8UBUOvQjUAgEBDsT5gHbUk03BBZ1TVARU7gBsSCJ5roToCG5OuZnPsBP4hbMsCX6ppbPzWPL2pp5eSCT5WiS8X9q6RNuib2BL2J8yfI7Am1k02VJ9oILKbiJMZJKkznoDHwx1+8WYi+ke4Nmn54A/Qv5sAAAAAAAAsauLiv7V2xq4uK/tWsPL08r8zVuk6l81l1fSR0YMWhz2dVGVNhqRkC2Vsp0UiLCIthUFiwqQooAAAooAApYBYAU3UAOywbZruKkdF38jdYgBQFAAUABUBVAAX2B0FN1TNVAFAIz7EAEKfFQS2qx0FAiIAFIVFz9oFgUUD2KCKABBBKqKEbILsRpmigGki7KGQRoAbqiqAAoAgKAAAKfA3OwoZACxkaHxJ+6AIOkm6wATe58SNQC3UXcCPLUsl10zA9lhddpI9ttwJynoee8m1jfqBufcR95tlYFkunsUA/gHwAlcjPQnUU2Lbwa3LAtrodzbIFvkdtTWc9TeLgHc1LZgbFtYU7Aim2oAAgC2LCkdHZwmJ4ommdnGywqvBXFW0arFwuq9MY0VeKmJhlZp6PuBYsqKeaKKbBv5ghY6gKTAdwCPI81hNYA8pF73zL69AJTaVOyB7SNAA2CbLOoIF/ctoBIBQRQ9gIuwgLHmB5gbdZDe6gmYWUE7BOygmVhQEJUtlYEle4QASG+oJrC7HcsCadlABFAPYAAeRIBqFsgBJU1AOxsZgkk6KgHdQABAUsFgQ0U3ARTSwCbLoAnmWWYQA3ACwumqARBY0mwBE3gIzi4B5J7FATbRSdCdAIVInOyoAACT5KKMbSyAEtCToySYugx1c+Pw8TF6NXTYVLJXlzFptOqO/GwacSLxlU4q6Jom1UM2acrjpiAiAKCAAKigCKCKigAAAAigAACKAAAoAAABBqEgAT9wBMAAAB2FhBAAUBbAgAC3QAmFS5IGS7AB3NBNwVBdgTzFNgMk1nNdk2EVDYFDfJUBUXYtkCG1l7nmCeQuep5SCGsmwBGosmoJvmL3SfIQAFAN8gF7pn0NLCBFty3UFIIg8iAMsw7HmIEmgAL3QF07oApuSEdZEIAFNwBAWE0kUW6WyAIzXI7AIvY01ABJyXYAzgz1AA2IA0LZk2ANiTuqCa7qgALpIAHxAAAA3O+YBMdD7yBTUFsgi7eRtpoAi2RQOxrB3LAEBqKZgdwI0JU7SCLaxuIAEga6B7AVQIQALAAoJoKQKAAHUAAVBFAAAUAAARQCAF+BYygCYO2q69zYQ2zVNcllADuCmwLogBIACioprGQAAKAIKHcAAsALICWUEDbyLbkk+YpuXX4AB3IEA2F2AC/U3FFNADfINyyBpsZ+w8zyA7wupBugXBQAIABUUINwBYTZbgCiBGQApsAAqKAAigAC6JdRSBFQJDuAsCALYDRFWNAAICDcFsbBsAeQIq7EAAACoKgAAAApAIHwBRQBAUAAWEVFCwACAoAAAKQIp2ABRFFAEAABUUUAQFRQAEAABUUABFAWARbEEABuu6CCnYUAAAAVFRQADutosRqW1BdDdM5uu6B2VFQAAAABRAAAAgBYBFNAAAAAEAAAAABAAFAAAEAAFBEFDcBAAJAAjqH8TbMCTeDYQQOgBdFlAXqn3rqn/ZAt1Ni226dgNjU3kBAQCMgknOLIE90lUtYEJuFrZgk9Ikm+0mW0QbTmCTe05JZbZ2PMEynomca6L5ZICAmVvaB8EnPdlab5Me4J7AS2YACbH54A/RP5qAAAAAAAAsOLi/7R2w4uK/tWsPL08r8zRMZsgdX0qyoi9VnTOsNGBH0rt243irJiyKtAAZIqCxYVIUUAUAAUAFhUhQAUUgFAhU9qxcU6KALAAoCgAKooIAp2FAt7lBFBQ+CooB2WCNdACNZUgC/RUjyLQKqpke0FA7Au4AqiKABcC6kApoZEKAIqgsdjMAABQFABFFQBQAOyooHfM2LgCpvddBS+UmxPT4gLvkabZHcA6i75HsA6H3hsBvsb9BdARd+qLv5RuBta4bZQs7gm3ku8E31MuncDOfPMjM3sbx9wF88z2LneLpv1BSCx1yFPI6lsstTTuAuxGoAACz55gQAG1zsBOYCAsIsCqAokpbJSUSurg8T9WZdjyqavBVEw9LDr8dETGrcdsbuMxI0us6K2ACgEZ7gdwAF2SPjkv/ZAJzADICAPidL6nsNwN12TdQBJJ3BTKYNsgANQDI1jrcADuqW6gdxQAsQmwHsFATzUzACAAjII0OwAAGgAAeYAABubKmYAKCAAG4oIFgAAAADYAAFBJO4AEBABAAaEgBKKABYA3RdgCyC9ASRU3zBTyTsdwPaBcE3ZBAAT5AACAAAipMXAvCLZFBhiYcVxaqGegDzsbCnDnPTq1vUmIqiYmLuPHwJpvNOcJY55Y+jnVFZYRUAXdBQBAFQUAAEUAABRFAAAAAANgANQDuHYQBRTslydSQO8i7JsBF9AznNfiCayKAkXA3BY0PgAJdTugGS6SdksAtyU0AL+9UuC6m+YXA2RTUDdBQOp8BAMhdEuCm6ABrK5+47AkAoCdlSABQEk2F84BCy6ICwaaIt+gIQd9AAyN8gDoT5Ba+mohou+aZwbAGYbgEmVyMhV7J5LGqAXF0QAFj7xEAFVBZBF0NZ6gBCLuAABBuAAEASG4BuZEGiCm6G/kApsQAB8AOwAAAoGkgG+QABKgAT3EADzAAFX2ZIqXzA7HQXZAgAAIIAF3QUUEAAAOwAqKKAagBuAAIKAAAKAAACgAC7pGq75oEzlYj2DKOwMey94U2QEWNIUEkUgCNM0UQDYUVFDYCAgFBQEURBQUDVIWQAnyIEDYNV1FDOUjYmQXuXNjqAF9JsqAkLfI2FDqTACk6oqACgRmgsXAjQgVAAAARVCAFgTusgEAgKEigAAKCKbCKAbAAWABYRUWAAFBTbMFQSMhQCDueQCkAAbAimxCgAAAoAAgAoIaLuIB2FFANZQDYUAAUUEABBUFBFAA+JAKoCAEAq7AAAIAKKAICooACAAAAAsAgAQKSsgAAgonW6igAAAAKAAii5EL5RAJrubGsrCBBqLuAB8EAAAVAFRUANgBUVFAAAAAEAAAAABAAFAAAEAFAAAAQAAQU3BNjQ7gAHwQIABAAO5c3JBOy7kkoJ7UyUA6pORrpqAgAITrCpKAi907AJKptPmBN8ktfrou02t5JuCdU7fcs6djSQT3dUy818kBLd0yv8A9V6rN7gxTeywWnogl7IrGQW8haAH52A/RP5qAAAAAAAAvRxcV/au2M3FxX9q1g9PKfM1bmxusReYdX0r5b8KLUM4jMjSCnUdJ4ZWgAFgIXcaiC2TcFABQFFAAUAFAUVFgFOxYjUVYO+pqWzBYBQABRQAVFFAAIUBRUUADZRSNcw8wPiqfBbRcF0n+AR95uKdlADRQALZKCgAKAAbgCiKKAqgpsAEEgKgKKAigACgAaigBuQAabC+wU8zUt2IA2zVI6qIEaBCKtgJAAAibwECi66mshuBGUkLnrlZAXS07lpjqigZaWyO+QXAWCOxnluAa5GuoKRY3iFj3G0WA0znU7HxAO2qm+hoCe1e5vmABfIAjsp+BGgCgKAAACI6eExPDV4ZnVzkTaYnoNS6r1Z1sMMCrx0R1ZxnLUd9gtkFDciLrYFtCTqyYzGYEZytiIsoJYsoCSiyZWBFRQIAA3A3AOhlOh3A3Nsxb5Amin8CACdw3BFAADQCwAB3AAFsCCoBuQKCb3UhAFAAAAAAABLKAIooIKgigAigACiCyIIoAnxUAQAAVAAAAAJAkAADfU+J5AEAXyBNBZtYBFNjYEi5soCQSbkASdVhJ8gC4bAAoJYsoCWhNZz0ZEZRYHLj8PE3qpy8nHMTTNqtXqzq042BGJEzEfSSxi4fV56rXRNE2mEiYuzpgCdS4BYAAAAAAAAAAAAXQEAA3FtsgE6gAvdDIAAA1FAQX7jYCEXzg31AQWAOgFgAMtgCTuAllsHsAt0RS+YJrqugAIoAa6ibALfzLnQA6gB3EXICfMkNgRU21WQAQFv5GwR5ggL2BFRfOwIbLtKAT5CpM3Bd80gmTWegGskfcAgBAobrF0AXMQAt00AADSQCABd0O4ALub5AndTa4BPkCAtzfM8gCfuDfQADYAAADY3Be6Agoigiz7g2ACAADYANAUNCNQBQ1BO662ITsgsGxY7AZhvmW2Amx1VBQLr3AAQAAAuooikAB5CABALugoqKF/IAAAFQAAABQAAAAAUW2REXLSgsQaSbeZlfIDJdEk6IKbmsn/YAhbAFjoi5oHmGZsKG6gAAoqHmgseYGoFwgtkAAB3UJRSwbGQBAvtA7luhBGoEQsZyhZBex1TZb+QpsCgILCAHUBcuiCwB5B2VBN1IAFsgirAEAWBQLEGpZBbACgAAAKAigKCAAL2RUU3AAWCbWNgI8yAnVFWwkKAC2BNlAAFRUgFAAAVAFAQAIAVFQABRQAIFQAEBUUUAABUEUAAIFUBAAFFAABABRUXZFABUARQAEAFBFRUAAUBQAtmbAAqKigACggKigAAQdwWSNCNdBBfiRkW94AqQqABsAAAKIGwAG4AEKCKAAAAAIAAACAAKAAAIKioAoAAIAAAAAIAu6CABuCfwFATyudl2SAJ+8NzpdA69U65qmuoG6TmqbXAnXM3VEBBQRNVlNwNzY3hJAndJjaVJ1m2orGdP4E23hd4n4ppoiHxTe0mn/U3BP+58Cc9NzcGM9zp0VO1sgSSbb3XVAScspRdNkkAPZAaH52A/RP5qAAAAAAAAsauLiv7V29HFxX9rHZrB6eU+atW7PBi8sN27Ai2bq+nrbdJGoDpJ2UFEI1XeAGoqKgCooCoqhAQoAdlFAUEWBYA7h3XSBSFT7lBQBQFA3AFURQABVgjc+8A2UFAFAPvFnIDZYTP2LuAFtFFFhDXQFABdwBSFRQAAUhLKKKgCmobKLAW8zyABVABAAFAhQDckgAUA3MgAhb2k3sa/AUiDY3yXeNgA2YoMlgALXNAAAAhfYkKoEa6CgRlvZLRHsPgu4G5Oslto0ufAF/nNF84M9gNZk01MvM7Ci5ppqoGtjXPYyNQOmpY0MpgBc75G6AvYj4EaHnAG/VczsT7wLaibqCgCgAAbEAExeAEb+FxJoqiOrvy1eTpnGr0OFxPHh2nVdu2N233YzqLsreynVkxjZZFUYzrDIABAABC2U7goG+pb2AAanYDchZQF0ABFLAAbHtAJAADcAUBFRQSFAABQAAAAAAAAAAAAAAAAAAAAAANwAAAAAAAAAAQCAUAAEUQRYAEFS2YECgJYFBAABUA0ABFCwCeS7AJOqgCLJYAkAABBJIUXY14lFOJTMTGbgxsGcOctHpsKqIqyqziUsSzby9R0Y2B4JvTnDRM56MuV7AAAAAAAAAABYAA0AFQgAXzASAlQJRZJAQXrAF+iHxXQEXZLrAHmgu4IvdF1BBQD7wACbwGwJbzF2NQNg3IA7BGoAGhcAgOwHsO2wAG+YAQW1ADZN1ARS2ZqBqFrgH8U7qASWO4AdhIBTYBA8zXJBVLmsgB0Ne4CB3AAXyBNVlADtILqBqeaAGy6ZEmwE9TSx7QAEBcgNQMzyDcA26gBseWwAbAb5gdjyPIAOwoCKIIKAASAAAQApmHddJBF0TcBdwNkCDcNgX4JIQB2NVmEjUU7KAHmGwAECBJ3AVYA1ALAgKJsAuYCgbgHmHU2AUQFAQABQAAAAAUDqtkCy6JktstQNVLCIlvNfItaAULXiVASywABC+1EVUhQAAUBQQFQAiDYA7ABC3O4BASIoamui2ARSwGxqWXYABAAFXeyGigAIApbzA1LhaEFEhQABVIBA2NixALEZGdwAhQRQAAAFARQAAAAFRSC2YAbqkKBkaGwikKigmqgAsgAFhFFj7wAAAAAUEAAFQVAAgUUANgEFAABUU3AA3AQFAAAVRFQABRQAAQABRUUABBQAAEAABUVAAFFAAguAQQKihsAAACoqAAKAAtpNYIi/cibIFlz3ygABRAAAIABUVAAAAFURUAAAAABAAAAAAQABQBAAAVFAAQAAAAAAAEDQ+4ATbNRM7AAAaIoggqagJ7V7gIW9oTsioam4ITsioAbmwKnknksGuoJPmdepOmQCT52M47ls9feiImvsLLtqTOcXBjZJj3Mt4Y/wBJXfzMgEtki9fNMgTqk/es2smoHtEAfngD9E/moAAAAAAACxq4uK/tXbGri4v8AtWsPL08p82mqM5dOHH0bS58OLy67dHWPqY+psKWVuClhE0sLZIUaEVAXcBRQAFABQFFRQFhF3FNYWNU1ZAAoAECigACigACoooCgAKLsGsnUBU7ruBSuexuAKblsxSFRQIXsi9hQIUAAAFAINgUVFULZBCwBIKCKIooAoAgoAGwKAdjIA6ioKvsM9SMjbOQXZNVtub+QJOiMrZFkFAAS/kpcBYSywAAoHsDyBS2eRP3yaABC6+wEmy7xB94BbI+BHkQKQu2ZHuNgI1DYA9iou9wDuaHvBc/ahssgbnsTpYmAWFTdQABQAAAAAFp1u2cNX4MTP2tWd8l6iyvVytE7STDRwmJFWHadYb4zhp2ndYVIUVLKIKoigAAk6FlATXQjJd9AAsbgAAG4SABlcsoKgAoAioqBIAACgAAAAAAAAAAAAAAAAAAAAAACggAAAAAAAAAAAAAAWAAAAANwAAAAAAEEFgBBQEFFEDYlAAAkCwJuoAAKACAAAk6WUVKxtlbZzY+BeJmj3OoiLTeEsTW3lTE06jux8GKpvu466ZpqmJizOmLLGICJsAAAAAAAnuAsdEAI6AWyAABdEUBFJ0NouCAvUAvmfzYgEXYARdwARfifEDyRfvADcktmAX3JANzzADYjUIAPaTobQAdSADOAzIAJNZAEU1A2zNgA2Rdzy3AA3AIPIkDzJRewHvPM65nYE3U0APJFk+IG+RHWDc36AhsuiAbC6ZEaAQB3AvnmQJIC/cE6gfxJNZ6AEbJvmSsRkB5mxZAUNiADzgAC4RnkBBAQAAAd13QAAFQVAPI3AAO0gARuAElwFRRU7Gi/cm4BC7IgoAGx2NgALAFlRYFQ+J3X2AiggAAAopsQAAAACCpsdVFMs5CAQLAKLAgKIsIAAoAAAAAKBsuyCW0ZR5sbL7AXqakQRoB0XQ0N0CBbE+YAi2sgi7hkKbLmlgFAFAUABAPYGgHwBdQLBnqZgAdkUWczyPKADcLewCA2sQC66lkjJUCPMO52FCVS6Cmepse0A0g2UEjNY7CwgAAAQKAsaoBBK7Aix0IgnICPNUWEUgIAAAFRUUAAAA2IBFWxYAPYGVlA3N0WUUjzLLugCwaAEBv5qAEgoQqILIAAAAoAAgGymyCWUBRQABYQRdg0ABUVFNwABAUAAABQUCBABRQBAAAVFFCAQFRQAEAABUUA2BFAUAAABBSAFAAAAFBFAWIBIXRLZrtIGui9k02XVACc8gFNy1xAAAABQEAABQRQAAAABAAAAQAAABQAAFQEUAAQAAAAAAAEAAAAENrG4CygIJuoAQkFzcU8jzDT3IISGwHVN16p5gXABAOyCTcIzjUnNQ0tdJmP+x0g6oJPnpYn7jKYkn/oCfxTfPqu8WjPodegJN7JOptnJp8RETZZ/gToCb9kldEz8gJ8/uY7spizHYC3mIA/PAH6J/NQAAAAAAAFhxcV/au3aHHxf9rHZrF6uT/5iYEXdENeDFqGyHV9TH5RYRYFUFGkhQAAA3BVBUUAFAAFFCAIZJqR5QKuikeYCiKKAoACqKCAAKodlBFBQO4oG+obFumgHwXsZnkCqlrqKAApsAEKAqiKABGoCwGugobigaFgUIU7ACiKKAAAiigABAKQiz3uAe0BSF3M/IgDSCLGV9FA8iNI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## 3.2 Simulation Running

In the home directory, there is a LunaSim folder. Enter this folder:

```Bash
cd ~/LunaSim
```

Run the one-click simulation startup script:

```Bash
./start_sim.sh
```

Wait for the simulation to start, the robot stands in the simulation environment

![图片展示的是Luna SDK中Dance Motion Simulation的云桌面验证中，机器人在模拟环境中的状态。画面中机器人位于网格背景的中心，姿态为站立，双手自然下垂。画面左下角显示了Time、Size、CPU等信息，右下角有Robot Velocity的图表。该图与文档中“Dance Verification”部分对应，用于说明在完成相关操作后，机器人会在模拟环境中执行动作，以验证Dance Motion Simulation功能。](data:image/jpeg;base64,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)

## 3.3 Dance Verification

After the simulation is started, open the browser and enter `127.0.0.1:8080` in the browser address bar to enter the robot configuration interface

![这张图片展示的是Luna SDK相关的机器人配置操作界面，整体为深色界面风格，左侧为功能导航栏，中间区域显示带LIMX Luna标识的人形机器人虚拟形象，右侧分为设备信息展示板块，上方是基本信息栏，标注了机器人名称、ID等内容，下方以绿色进度条呈现内存占用为9%、CPU使用率为21.7%的状态，该界面对应舞蹈验证环节中，打开浏览器输入127.0.0.1:8080后进入的机器人配置界面，可用于后续模型相关配置操作。](data:image/jpeg;base64,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After observing that the simulation connection is normal, select Model Configuration

![图片展示的是Luna机器人配置界面中的模型配置页面。左侧导航栏有“模型配置”等选项，当前选中“模型配置”。页面上方有“模型列表”“动作”“竹签”三个标签，红色箭头指向“模型列表”标签。下方是模型列表区域，显示了多个模型名称、动作、竹签、模型大小等信息，如“Luna_1000”“Luna_10000”等，部分模型右侧有“删除”按钮。该图片与文档中“Dance Verification”部分上下文对应，用于说明在机器人配置界面进行模型配置的操作步骤。](data:image/jpeg;base64,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Select "Select Folder", select the folder containing the trained policy.onnx, reference trajectory reference.txt, and configuration file param.yaml, name the action you added, and click Upload:

![图片展示的是Luna SDK中Dance Verification步骤中模型配置界面。界面中“模型配置类型”下，有“Luna”和“Luna_1”两个选项，其中“Luna”被红色框突出显示。下方“模型列表”中列出了多个模型名称及对应信息。该图片与文档中“Dance Verification”步骤相关，用于指导用户在Luna SDK中进行Dance动作验证时，选择正确的模型配置类型。](data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAYEBQYFBAYGBQYHBwYIChAKCgkJChQODwwQFxQYGBcUFhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSj/2wBDAQcHBwoIChMKChMoGhYaKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCj/wAARCAo2E0gDASIAAhEBAxEB/8QAHQABAQADAQEBAQEAAAAAAAAAAAQDBQYHAgEICf/EAGoQAQABAwECCAgHDQQGCAIAFwABAgMEBREUBhIhU1SSoqMTFjFRZJOh0gcVM0FSYdEiJCUyVWNxcoGDkbHBNESC4SM2QmKywgg1RXN0lLPwFzdDVvF1lSZX0+IYRoSkJzhHSPJmlrTD1P/EABsBAQEBAAMBAQAAAAAAAAAAAAABAgMEBQYH/8QAQxEBAAECAgYJAgQEBgMAAgEFAAECEQMhBBVRUpHREhMWMUFTgZLwYXEFobHBIjIzNAYUQkRy4SNG8TVU0iRigqLC/9oADAMBAAIRAxEAPwD+eAGmQAAAAAAAAAAAAAAAAAAAAAAAAAEeb8rH6qdRm/Kx+qnAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABtAAAAAAAAAAAAAAAAAAAAAAAAAAAAR5vysfqp1Gb8rH6qcAAAZ8HFvZ2ZZxcaia716uKKKY+eZe36D8FujYuJR8bU15uTMba/wDSVUURPmiKZif4ykzZ5v4h+K6P+HxHXXvPdEd7wket8O/g0xsTTr2oaB4SnwNM13MeqqattMeWaZ8u36nkixN3LoOn4OnYfWYM84Ad9oGLj6j8GesUxYtTl4lzwkXOJHHinkny+X5qltlM7Hd8YhwI3fA7RI1/XrODXVXRamJruV0eWmmI+3ZD54XaN8Q69kYNNVVdujZVbqq8tVMxtgmLREkZtMO84U4uPp3wfaDZixapy8mfC13OJHHmNkz5fL/tQ0ujcDdb1jFjJxMTZj1fi13K4oir9G3ln9PkWaZvMbEvlE7XOrs3Sc3CwsXLyrE28fJjbZrmY+7j9G3b8791jSM7Rsrd9Sx6rF3ZtjbsmKo88THJL0TXdA1HXuCXBi3pliLs27G2uZrimKYmmnZ5ZIi8Xg8bS8sG517g1quhRTVqOLNFqqdlNymYqpmfNtjyT+l1fBnHw9G4C3uEFWBZzs6bvEo8NTxqbcbdm3Z/78pEXvfwPo87HZ5nD2/n4GRi52k6Zci5RNNFVFuYm3M+SeWZ8n7HLadgZWpZdGNgWK79+ryU0R7Z80fWls7QqUdNqXAbX9PxJyb2Fx7dMba/BVxXNMfXEcv8HNU0zVVFNMTNUzsiIjlmT6D8XabpObqVvJuYVibtGPR4S7MTEcWnl5eWfqlvsb4P+EWRjRejCpt7Y2xRcuU01T+zbyft2Nv8Hli5jYHCyxep4t23jTRVG2J2TEVxPLC2777JTY88Gx0fRdQ1iq7Tp2PN7wVPGuVTVTTTTH1zVMQ+NM0rN1TO3TAsVX7/AC8lExsjZ88z5Nn17UtJdCOl1bgTrul4dWVk4kVWaY211Wq4r4sfXEcv7Wy+DDTMbU7+rUZGLayLlONPgouUxOyqeSJjasRMzYcQN7q/BPWtIw6svUMLwOPExTNXhaKuWfJyRVMtEyoPR+BGjcHbGbp05uZb1HUcqONbxrdPGt2uTb939cbPJP8AD53H8L7dFrhRqlu1RTRRTkVxTTTGyIjb80LVFrJGbUD0e1OLwK4K6fm0YdjJ1jUI48V36eNFunZt5I/RMfxY9VoxOFnA7I1q3h2cXVMKrZfixGym5Tycuz9E+xZptf6EZ2+rzwd5wRw8LSOC2Xwl1DGoyr1Nfgsa1cjbTt8m3Z+n+TY6TmY/D3Cz8LPwcXH1Ozbm7j3seji+T5p2zM+XZ8/zk08SJeZDtPg+0fDvTqOq6tai7iadRx/BT5K6uWeXz+TyfW3Og8IsXhbqE6NrGl4VuxfpqjHrs0cWq1MRtjl/RHzbDo+HiX8ZeZDrODfBeMzhrc0nLmZsY1dc3Zjk41NM/wBeT+Lexwzwp1r4r+J9P+I/CeA2eD+62bdnG831+T9pEXt9Scr/AEebDoeHWi0aDwivYtjbu9URctbZ27KZ+b9k7Yc8ysxYWaVpmZq2XGNp9mb1+YmriRMRyR5fKjX6Fbrv6viWLd65Ym9dptTXbnZVETOxqmLzZJm0XbfxE4Sfkuv1tHvHiJwk/JdfraPeT8I68zSdczMG3qOZcosV8SKqrtW2fa1vxnn9OyvW1fal4WYmGfWdC1LRZtRqeLVY8Lt4m2qmduzy+SZ8770DQsnXJyqMKuz4ezb8JFqqrZVc+qnzy6Dhvcru8FeCtdyuquuqxXM1VTtmeWGn4N6XrtV21qeiYt6ubNf3NyjZs2x5Y9q2/imEmcolqbWFlXZqi1jX6+LPFq4tuZ2T5pbjW+CufpVGHNVFd+vItRdmi3bqmbe35quTyul4IZWvalwxyqZrrw7UXZvZtqxRxaYmOTZs5eWdmz+Lc01cKNTyNbyaq9TwLdqia8OxTRERXPzU8scvkj+K9HKJPF5TewsuxRx72Nft0fSrtzEe1dwe0arWbmZTTeizu2PXkTM07eNxfm8rY8IsrhVuEW9dnNpxLlURsvUbKZqjlj5nQfB5kaJNnNoowsqMunAuTkVzd+5rp5NsUx8yRHf88DY8+x8XIyNu72Lt3i+XiUTVs/g3GRwX1C1ouNqVFq5dou1zbrtU26uPbmPPGzyT52+4MzqFGqxmcGNPz40Su5TTeteEiZq2eXl/a6W1hcKquFlVnfs34mpucfwtWyJmjy8Xybdvze1Ypul3kuRiZGPETkY961E8kTXRNO3+LA7Lh5Gv37l2/qOPl2dLpvT4Cm9VE8Tb5OXy7djjWGpAAAd18HPAeeEs15edXXa061VxfuOSq5V88RPzR9ZM2dfStKwtEwpxcWbRDhR/QWT8GPBq7izatYt6xc2bIu0Xqpq2+fZMzHseNcMeDuRwZ1ivDv1ce3Mce1diNkV0/akTEuhoH41o2n1zh4d4q2T8logbfgldtWuEum1ZFFFyzN6mmumumJiYnk5Yn9LdMXmIetM2i7UDp/hHwKNP4XZluzbpt2q4puUU0xsiImPmj9O1bm8DIx+A1nW4uXZypim5XanZxYomdkT5Nu3ySzHddZ77OLHZ/BVp9nN4SV15Vqi7Yx7FVyqm5TFVO3kiOSf0tFRg5Wva5kW9LxZuV3blVdNFuIimmnb/AAiGpicvql+9qV2laVm6tduW9PsTert0TXXETEbKfPyy2+rcCdd0vDqysnEiqzTG2uq1XFfFj64jl/a3XwQUzXqWq00xtqqw5iI+vbBEXmw4F+OsvcAOEdGNVfnBidnLNum7TNez9ETy/o8rX8ENLt6nwow8DNiqm3VXPhKZ5J5ImZj6vJsIpmZsTNou0Y9I17hhc0DWcnTdL0bTbONj1eD2XLM8av6+SY8rjOEmrUa1qO9UYVjD20RTVRZjZEz89U8nllMvBbbWqHS6VwI17U8SMnHw+LZqjbRN2uKJrj6onl/a0up6dl6Xl1Y2oY9di9Ty8Wr5488T5Jj64JiY7yM0j6opmuuKaY21TOyIbXQuDmqa7NXxbi1XKKZ2VXKpimmP2z/KFOp8GtT0DMw51K1RRRduxFFVNyKomYmNvk5VinOLpM5ZNZqul5mk5MY+o2JsXppivizMTyT5PJKJ3Pwu01V8LqKaImqqbFERERtmZ2y5fWNFz9HqtU6lYixXdp49NE3KaqtnnmImZj9rKy1w6jT+AvCDOxKcm1hxRbrjjURcuU0zVH6Jn+exo83AydOz5xc+xXZv0VRFVFUf+9sfW1ab2lL5XRj03hxwJzcrUMavg9pdqMWLFMVeDqt24422fLEzG2fJyvOMvGu4eVdxsijiXrVU0V07YnZMeWNsJMWm0r9WEbngzpmBqOTdnVNSt4GNZp49U1RtqrjzUx5/4/ol1nDnG0mjgTpF/RcaLdiu9MU3KqIi5XERVG2qfLO2YWYtT0kjObPOh1HweaHY1vXZpzY24ePbm9djbs42zyQ6HA4Y4ep6zRpOVo+BTo16vwNumm3sro28kVbfJ/CIIpvaPGS/i82HX3eCkU8P40Omqrd6rkVRV8/g9nG/js5G71Thdh6LrFekYOj4FWk49fgbsV29tdzZyVTt8n8YkiLxH1Jyl5qOv4e8HrOna/jU6ZTsxc+mmuzT81MzOzZH1eT+Lf69qmNwFqxtK0nT8S/keDivJv5FHGmuZ+bkmPsLZXn7Hjk8xHc8OdOwcrRNO4RaXj041GX9xes0fi018vLH7Yli4I6VoFNGFmaznU5F6/dii1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When the model list shows the newly added action as shown in the figure below, you can click Execute, and Luna will execute the action in the simulation

![图片展示的是Luna SDK中Dance Verification步骤中模型列表界面。列表中包含多个动作名称，如“跳跳”，“爱情鸟”等，每行有中英文名称、执行器、来源、时长等信息，右侧有“执行”按钮。其中“跳跳”动作被红色框突出显示，其执行器为“open dance”，来源为“本地”，时长6s，右侧也有“执行”按钮。该图片与文档中Dance Verification步骤相关，用于指导用户在模型列表中选择特定动作进行执行操作。](data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAYEBQYFBAYGBQYHBwYIChAKCgkJChQODwwQFxQYGBcUFhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSj/2wBDAQcHBwoIChMKChMoGhYaKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCj/wAARCAVsEdYDASIAAhEBAxEB/8QAHAABAQEAAwEBAQAAAAAAAAAAAAQDBQYHAgEI/8QAXRABAAAEAgUFDAUIBQkHAwMFAAECAwQFFBFTVJKjBhITIWQVFhcxQWWToqTR0uIHJVFhYyI0Q3FzgZGxIzJSgqEIMzZCYnKzwfAkNTd0g7LhVXXxJlZXlJXTRML/xAAaAQEBAQEBAQEAAAAAAAAAAAAAAQIDBAUG/8QAPhEBAAIAAgULAgQFBAIDAQEAAAERAiEDBBIx8AUUFSQmQVJUoaLRUWETcYGxIjKRweE0NUKygvEjM3Jzkv/aAAwDAQACEQMRAD8A/ngG8lKWWSE9eMYQj4pYeOLTLAUdPLD+pQp6P9qGkzP4NHdUTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBOKMz+DR3TM/g0d0E4ozP4NHdMz+DR3QTijM/g0d0zP4NHdBO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wHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4TvywHb+DU+E5zrPg9JOhuSPMe7D8PPu83Htg41P4jvNx7YONT+J6D35YDt/BqfCd+WA7fwanwnOdZ8HpJ0NyR5j3Yfh593m49sHGp/Ed5uPbBxqfxPQe/LAdv4NT4Tvy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)
#（注：内容由AI生成）