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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.ROS2 install Humble

2. Installing Humble in ROS2

  • The ROS2-Humble installation supports Ubuntu 22.04.
  • If you need to install a different version of ROS2, simply replace the humble version identifier in the installation command with the corresponding version. This applies to all other ROS-specific software in the ROS2 tutorial series and will not be covered in subsequent tutorials.

1. Set the locale

First, check whether the locale supports UTF-8 encoding. You can run the following command to check and set the UTF-8 encoding.

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locale # Check for UTF-8 support
​
sudo apt update && sudo apt install locales
sudo locale-gen en_US en_US.UTF-8
sudo update-locale LC_ALL=en_US.UTF-8 LANG=en_US.UTF-8
export LANG=en_US.UTF-8
​
locale # Verify the configuration is successful
​

Note: The locale can be different, but must support UTF-8 encoding.

2. Set up the software source

Start the Ubuntu universe repository

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sudo apt install software-properties-common
sudo add-apt-repository universe

Add the ROS 2 apt repository to the system and authorize our GPG key with apt.

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sudo apt update && sudo apt install curl gnupg lsb-release -y
sudo curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.key -o /usr/share/keyrings/ros-archive-keyring.gpg

Add the repository to the source list

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echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] http://packages.ros.org/ros2/ubuntu $(source /etc/os-release && echo $UBUNTU_CODENAME) main" | sudo tee /etc/apt/sources.list.d/ros2.list > /dev/null

3. Install Humble

First, update the apt repository cache:

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sudo apt Update

Then upgrade the installed software (ROS2 packages are built on the frequently updated Ubuntu system. Please ensure your system is up to date before installing new packages):

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sudo apt upgrade

Install the desktop version of ROS2 (recommended), which includes ROS, RViz, examples, and tutorials. The installation command is as follows. If you need to install a different version, replace "humble" in the command with the corresponding version number:

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sudo apt install ros-humble-desktop python3-argcomplete

Install the colcon build tool

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sudo apt install python3-colcon-common-extensions

4. Configure the Environment

  • If you are using a different version of ROS2, replace the "humble" version identifier with the corresponding version. For example, for the foxy version, replace "humble" with "foxy" in the command.

When executing ROS2 programs in a terminal, you need to run the following command to configure the environment:

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source /opt/ros/humble/setup.bash

You must execute the above command each time you open a new terminal. Alternatively, you can run the following command to add the environment configuration instructions to the "~/.bashrc" file, eliminating the need to manually configure the environment each time you start a new terminal.

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echo "source /opt/ros/humble/setup.bash" >> ~/.bashrc

At this point, ROS2 has been installed and configured.

5. Run the publisher and subscriber example nodes

The ROS2 desktop version has integrated some example nodes. You can test whether ROS2 is successfully installed by running these example nodes.

  • Run the publisher node
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ros2 run demo_nodes_cpp talker
  • Run the subscriber node
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ros2 run demo_nodes_cpp listener

6. Run and experience the turtle example

The turtle simulator, TurtleSim, is a classic teaching tool in ROS. It helps you quickly understand core ROS concepts.

  • Run the turtle simulator
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ros2 run turtlesim turtlesim_node
  • Run the keyboard control node
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ros2 run turtlesim turtle_teleop_key
  • View velocity topic data
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ros2 topic echo /turtle1/cmd_vel

7. Uninstallation

After installing ROS2, if you want to uninstall it, you can execute the following command:

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sudo apt remove ~nros-humble-* && sudo apt autoremove

You can also delete the ROS2 repository:

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sudo rm /etc/apt/sources.list.d/ros2.list
sudo apt update
sudo apt autoremove
Introduction to ROS2
ROS2 development environment

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