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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

2.8 Using USB Camera

Using USB Camera

Using USB Camera1. Environment Preparation2.Execution MethodUsage instructions (default usb_pixel_format is mjpeg)3. Expected Results

To achieve environmental awareness capabilities, robotic products typically include cameras to acquire image information. USB cameras are easy to obtain, convenient to use, and highly versatile. TogetheROS.Bot adds support for USB cameras and supports standard ROS2 image messages.

Note:

To run this section, you need to first learn the TogetheROS.Bot vision application chapter and install the TROS environment.

1. Environment Preparation

  • Connect the power supply.
  • Connect the USB camera to the development board and ensure that the /dev/video8 device node is created.
  • Connect the development board to the monitor using an HDMI cable.
  • Log in to the RDK S100(P) via MobaXterm or other SSH tools.
  • Confirm that your USB camera is working correctly and connect it to the RDK's USB slot.
  • The RDK has been flashed with the Ubuntu 20.04/Ubuntu 22.04 system image.
  • tros.b has been successfully installed on the RDK.
  • Confirm that your PC can access the RDK via the network.

2.Execution Method

Usage instructions (default usb_pixel_format is mjpeg)

  • Log in to RDK via SSH and confirm the USB camera device name (e.g., /dev/video0).

  • Then, start the USB camera using the following command.

    x
    # Configure the tros.b environment
    source /opt/tros/humble/setup.bash

     

    x
    # Launch method:
    ros2 launch hobot_usb_cam hobot_usb_cam.launch.py usb_video_device:=/dev/video0

     

  • If the program outputs the following information, it means the node has started successfully.

    xxxxxxxxxx
    [INFO] [launch]: All log files can be found below /root/.ros/log/2024-01-18-19-44-39-419588-ubuntu-3951
    [INFO] [launch]: Default logging verbosity is set to INFO
    [INFO] [hobot_usb_cam-1]: process started with pid [3953]
    [hobot_usb_cam-1] [WARN] [1705578280.808870437] [hobot_usb_cam]: framerate: 30
    [hobot_usb_cam-1] [WARN] [1705578280.809851560] [hobot_usb_cam]: pixel_format_name: mjpeg
    [hobot_usb_cam-1] [WARN] [1705578280.936697507] [hobot_usb_cam]: This devices supproted formats:
    [hobot_usb_cam-1] [WARN] [1705578280.936858791] [hobot_usb_cam]:        Motion-JPEG: 640 x 480 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.936912830] [hobot_usb_cam]:        Motion-JPEG: 1920 x 1080 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.936960328] [hobot_usb_cam]:        Motion-JPEG: 320 x 240 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937007285] [hobot_usb_cam]:        Motion-JPEG: 800 x 600 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937053241] [hobot_usb_cam]:        Motion-JPEG: 1280 x 720 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937098906] [hobot_usb_cam]:        Motion-JPEG: 1024 x 576 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937144528] [hobot_usb_cam]:        YUYV 4:2:2: 640 x 480 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937190068] [hobot_usb_cam]:        YUYV 4:2:2: 1920 x 1080 (5 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937235858] [hobot_usb_cam]:        YUYV 4:2:2: 320 x 240 (30 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937282064] [hobot_usb_cam]:        YUYV 4:2:2: 800 x 600 (20 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937328020] [hobot_usb_cam]:        YUYV 4:2:2: 1280 x 720 (10 Hz)
    [hobot_usb_cam-1] [WARN] [1705578280.937373518] [hobot_usb_cam]:

3. Expected Results

View the USB camera image on the web interface; open another terminal:

xxxxxxxxxx
# Configure the tros.b environment
source /opt/tros/humble/setup.bash
xxxxxxxxxx
# Start the websocket
ros2 launch websocket websocket.launch.py websocket_image_topic:=/image websocket_only_show_image:=true

On your PC, open a web browser (Chrome/Firefox/Edge), enter IP:8000 (where IP is the RDK's IP address), and click on the "Web Display" option in the upper left corner to view the live feed from the USB camera.

USB 摄像头实时画面

Example of GPIO read and write operations
Using MIPI Camera

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