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RDK S100(P) Board📖
0. RDK S100(P) Developer Kit
  • 1. RDK S100(P) Official Tutorial
1. Introduction to RDK S100(P) Development Board
  • 1.1 Introduction to the RDK S100(P) Development Board
  • 1.2 Install Operating System
  • 1.3 Interface Descriptions
  • 1.4 Accessory installation
  • 1.5 Camera Expansion Board
  • 1.6 MCU Port Expansion Board
  • 1.7 Precautions for using 15.6-inch screens
2. Basic Settings 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 Example of GPIO read and write operations
  • 2.8 Using USB Camera
  • 2.9 Using MIPI Camera
  • 2.10 SSD mounting
  • 2.11 Binocular camera depth algorithm
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 model course
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 to 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 model course
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 agent 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 WhatsApp Plugin Application
  • 3.OpenClaw WebChat Interaction
  • 4.OpenClaw TUI Interaction
  • 5.OpenClaw Tools Introduction
  • 6.OpenClawGate Gateway User Manual
  • 7.OpenClaw Features Overview
  • 8.OpenClawClawHub Introduction (Skill Installation)
  • 9.OpenClaw Application - File Management
  • 10.OpenClaw Application - Camera
  • 11.OpenClaw Application - Browser Control
  • 12.OpenClaw Application - Script Execution
  • 13.OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 14.OpenClaw Application - Dedicated AI Assistant
  • 15.OpenClaw Web Search Capability Configuration
8.ROS2 basic course
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 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
  • Annex_File
  • Code
Download ZIP

Welcome to RDK S100(P) Board 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. Create a startup service (Systemd)2.1 Creating a Startup Script2.2 Creating a Systemd Service File2.3 Managing and Debugging the Service

1. Offline Voice Configuration

Before setting up auto-start, we must ensure the program can work independently offline. This requires modifying the configuration file.

  1. Locate the Configuration File:

In your project code, find and open the configuration file:

config/yahboom.yaml

  1. Modify Configuration Parameters:

Please check the following parameters in the file and ensure their values ​​match those shown below. If the parameters are missing, please add them.

​x
asr:                                    #Voice Node Parameters
  ros__parameters:
    VAD_MODE: 2                         #vad sensitivity
    sample_rate: 16000                  #asr audio sampling rate
    frame_duration_ms:  30              #VAD frame size unit: ms
    use_oline_asr: False                #Whether to use online ASR recognition (True uses online, False uses offline)
    mic_serial_port: "/dev/ttyUSB0"     #Microphone serial port alias
    mic_index: 0                        #Microphone Index
    language: 'en'                      #asr language
​
model_service:                          #Model server node parameters
  ros__parameters:
    language: 'en'                      #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'              # Current large model platform

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

2. Create a startup service (Systemd)

Now, we will create a systemd service so that largemodel_control.launch.py runs automatically at system startup.

2.1 Creating a Startup Script

To ensure systemd correctly loads 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
  1. Write the script content:

Copy and paste the following content into the script file.

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

Important Note: Please ensue that /home/sunrise/ in the script is replaced with your own user's home directory path.

  1. Save and Exit
  2. Grant Script Execution Permissions:
xxxxxxxxxx
chmod +x ~/yahboom_ws/src/largemodel/start_largemodel.sh

2.2 Creating a Systemd Service File

This is the most crucial step. We will tell the system that we have a new service that needs to be managed.

  1. Create the service file:

You need sudo privileges to create this file.

xxxxxxxxxx
sudo vim /etc/systemd/system/largemodel.service
  1. Write the service configuration:

Copy and paste the following content 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 
  • ExecStart The path in the command must be exactly the same as the path to the startup script to be executed.
  1. Save and exit.

2.3 Managing and Debugging the Service

Now that your service has been created, we need to get systemd to load it and set it to start automatically on boot.

  1. Reload the systemd daemon so that it reads the service file we just created:
xxxxxxxxxx
sudo systemctl daemon-reload
  1. Set the service to start automatically on boot:
xxxxxxxxxx
sudo systemctl enable largemodel.service
  1. Start the service immediately:
xxxxxxxxxx
sudo systemctl start largemodel.service
  1. Check the service status:

This is the most important command to verify that 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 something else, please continue to the next step for debugging.

 

  1. 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 using the following command. This is crucial for locating the problem.

xxxxxxxxxx
journalctl -u largemodel.service -f

After completing all the above steps, the purely offline largemodel voice service will now start automatically every time you boot up.

Multimodal autonomous agent application
OpenRouter large model API aggregation platform

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