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RDK S600 Developer Kit📖
1.RDK S600 board introduction
  • 1.1 RDK S600 board introduction
  • 1.2 System Flashing
  • 1.3 Hardware Interface Description
  • 1.4 Accessory Installation
  • 1.5 Camera Expansion Board
  • 1.6 MCU Interface Expansion Board
  • 1.7 Precautions for Using the 15.6-inch Screen
  • 1.8 System Boot Modes
2.RDK S600 basic course
  • 2.1 Network Configuration
  • 2.2 Remote Login
  • 2.3 System Update
  • 2.4 Boot Auto-Start Configuration
  • 2.5 RDK Exclusive Command Usage
  • 2.6 Linux Command Usage
  • 2.7 Examples of GPIO Read and Write Operations
  • 2.8 Using the USB Camera
  • 2.9 Solid-state mounting
  • 2.10 SSD expansionnew
3.TogetheROS.Bot Vision Applications
  • 1. About TogetheROS. Bot
  • 2. System Installation
  • 3. Object Detection(YOLO)
  • 4. Image Classification(mobilenetv2)
  • 5. Image Segmentation(mobilenet_unet)
  • 6. Perception Algorithm(BEV)
  • 7. Human Detection and Tracking (Ultralytics YOLO Pose)
4. Offline AI Large Model Development
Offline large model (Text Interaction)
  • 1. AI large model environment deployment
  • 2. Install large model dialogue platform
  • 3. Meta AI Llama 3.2 model
  • 4. Alibaba Cloud Qwen3 model
  • 5. Microsoft Phi-4 mini model
  • 6. DeepSeek - DeepSeek-R1 model
  • 7. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 8. Google Gemma3 Visual Multimodal Large Model
  • 9. Lava Visual Multimodal Large Model
  • 10. MiniCPM-V Visual Multimodal Large Model
  • 11. Multimodal visual understand application
  • 12. Multimodal text image application
  • 13. Multimodal visual localization application
  • 14. Multimodal table scanning application
  • 15. Multimodal Autonomous Agent Applications
Offline large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Offline speech-to-text (ASR)
  • 2. Offline Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual understanding voice interaction
  • 5. Multimodal Text-to-Image application
  • 6. Multimodal video analytics application
  • 7. Multimodal visual localization application
  • 8. Multimodal table scanning application
  • 9. Multimodal autonomous agent application
  • 10. AI Large Model Offline Voice Assistant
5. Online AI Large Model Development
Online large model (Text Interaction)
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal visual understand application
  • 3.Multimodal visual localization application
  • 4.Multimodal table scanning application
  • 5.Multimodal autonomous proxy application
Online large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Online speech to text (ASR)
  • 2.Online text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multimodal visual localization application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model online voice assistant
6.YOLO26 tutorials
  • 01.YOLO26 environment
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training - conversion
  • 11.Model prediction
7.OpenClaw Advanced Development
  • 1. OpenClaw Deployment
  • 2. OpenClaw and WhatsApp Plugin Application
  • 3. OpenClaw TUI Interaction
  • 4. OpenClaw WebChat Interaction
  • 5. OpenClaw Gate Gateway Operation Manual
  • 6. OpenClaw Plugin Function Introduction
  • 7. OpenClaw Tools Introduction
  • 8. OpenClaw ClawHub Introduction (skill Installation)
  • 9.OpenClaw Application - File Management
  • 10.OpenClaw Application - Browser Control
  • 11.OpenClaw Application - Camera
  • 12.OpenClaw Application - Script Execution
  • 13.OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 14. OpenClaw Application - Dedicated AI Assistant
  • 15. OpenClaw Configure Web Search Capability
8.ROS2 basic course
  • 1.Introduction to ROS2
  • 2.ROS2 install Jazzy
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
Download
  • System_File
  • Code
  • 3D_Model_File
  • Tools_Software
Download ZIP

Welcome to RDK S600 Developer Kit repository

10. AI Large Model Offline Voice Assistant

10. AI Large Model Offline Voice Assistant

10. AI Large Model Offline Voice Assistant1. Offline Voice Configuration2. Creating a Boot Auto-start Service (Systemd)2.1 Creating a Startup Script2.2 Creating the Systemd Service File2.3 Managing and Debugging the Service

1. Offline Voice Configuration

Before setting up auto-start, we must ensure that the program itself can work independently in an offline state. This needs to be done by modifying configuration files.

  1. Locate the configuration file: In your project code, find and open the configuration file: config/yahboom.yaml

  2. Modify configuration parameters: Please check the following parameters in the file and ensure their values match those shown below. If the parameters do not exist, please add them.

    ​x
    asr:                                    #Voice node parameters
      ros__parameters:
        VAD_MODE: 2                         #VAD sensitivity
        sample_rate: 16000                  #ASR recording audio sample rate
        frame_duration_ms:  30              #VAD frame size in ms
        use_oline_asr: False                #Whether to use online ASR recognition (True for online, False for offline)
        mic_serial_port: "/dev/ttyUSB0"     #Microphone serial port alias
        mic_index: 0                        #Microphone index
        language: 'zh'                      #ASR language
    ​
    model_service:                          #Model server node parameters
      ros__parameters:
        language: 'zh'                      #Large model interface language
        useolinetts: False                   #Whether to use online speech synthesis (True for online, False for offline)
    ​
         # Large model configuration
        # llm_platform: 'ollama'              # Optional platforms: 'ollama', 'tongyi', 'spark', 'qianfan', 'openrouter'
        llm_platform: 'ollama'              # Currently selected large model platform
    ​
    • use_oline_asr and useolinetts must be set to False.

    • llm_platform must be set to ollama.

      With this configuration, everything will be offline.

  3. Save the file and rebuild the project to apply changes:

    xxxxxxxxxx
    cd ~/yahboom_ws
    colcon build
    source install/setup.bash

After completing this step, the program is already a purely offline voice service.

2. Creating a Boot Auto-start Service (Systemd)

Now, we will create a systemd service to make largemodel_control.launch.py run automatically at system startup.

2.1 Creating a Startup Script

To enable systemd to correctly load the ROS2 environment, the best practice is to create a simple bash script to encapsulate our startup command.

  1. Create the script file: In the directory (~/yahboom_ws/src/largemodel/), create a file named start_largemodel.sh.

    xxxxxxxxxx
    vim ~/yahboom_ws/src/largemodel/start_largemodel.sh
  2. Write the script content: Copy and paste the following content into the script file.

    xxxxxxxxxx
    #!/bin/bash
    ​
    # Source ROS2 Jazzy environment
    source /opt/ros/jazzy/setup.bash
    ​
    # Source Yahboom workspace environment
    source /home/sunrise/yahboom_ws/install/setup.bash
    ​
    # Start largemodel control script
    ros2 launch largemodel largemodel_control.launch.py

    Important: Please ensure to replace /home/sunrise/ in the script with your own user home directory path.

  3. Save and exit

  4. Grant execute permission to the script:

    xxxxxxxxxx
    chmod +x ~/yahboom_ws/src/largemodel/start_largemodel.sh

2.2 Creating the Systemd Service File

This is the most critical step. We will tell the system that we have a new service to manage.

  1. Create the service file: You need to use sudo privileges to create this file.

    xxxxxxxxxx
    sudo vim /etc/systemd/system/largemodel.service
  2. Write the service configuration: Copy and paste the following content completely into the service file.

    xxxxxxxxxx
    [Unit]
    Description=Robot Service
    After=network.target sound.target graphical.target multi-user.target
    Wants=network.target sound.target graphical.target multi-user.target
    ​
    [Service]
    Type=simple
    User=sunrise
    Group=sunrise
    Environment=DISPLAY=:0
    Environment=XDG_RUNTIME_DIR=/run/user/1000
    Environment=PULSE_SERVER=unix:/run/user/1000/pulse/native
    SupplementaryGroups=audio video
    ExecStartPre=/bin/sleep 10
    ExecStart=/home/sunrise/yahboom_ws/src/largemodel/start_largemodel.sh
    Restart=on-failure
    StandardOutput=journal
    StandardError=journal
    ​
    [Install]
    WantedBy=multi-user.target
    • The path in ExecStart must exactly match the startup script path.
  3. Save and exit.

2.3 Managing and Debugging the Service

Now that your service is created, we need to let systemd load it and set it to auto-start on boot.

  1. Reload the systemd daemon to read our newly created service file:

    xxxxxxxxxx
    sudo systemctl daemon-reload
  2. Set the service to auto-start on boot:

    xxxxxxxxxx
    sudo systemctl enable largemodel.service
  3. Start the service immediately:

    xxxxxxxxxx
    sudo systemctl start largemodel.service
  4. Check service status: This is the most important command to verify whether the service is running successfully.

    xxxxxxxxxx
    sudo systemctl status largemodel.service
    • If you see Active: active (running), congratulations, the service has started successfully!
    • If the status is failed or other, please continue to the next step for debugging.
  5. View service logs (essential for debugging): If the service fails to start, you can view all real-time logs generated by the ros2 launch command through the following command, which is crucial for locating problems.

    xxxxxxxxxx
    journalctl -u largemodel.service -f

After completing all the above steps, every time the system boots, it will automatically start the purely offline largemodel voice service.

To disable the online voice assistant service, run the following commands

xxxxxxxxxx
sudo systemctl disable largemodel.service
sudo systemctl stop largemodel.service
Multimodal autonomous agent application
OpenRouter large model API aggregation platform

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