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RDK X5 Board📖
1.Introduction to RDK X5 board
  • 1.Introduction to RDK X5 board
  • 2.Write system file
  • 3.Hardware interface description
  • 4.Install case and other accessories
  • 5.Use 7-inch display
2.Basic settings course
  • 1.Network configuration
  • 2.Remote login
  • 3.Update system
  • 4.srpi-config user guide
  • 5.config. txt configuration file
  • 6.Self-startup setting
  • 7.RDK exclusive command usage
  • 8.Linux command usage
  • 9.GPIO readwrite operation
  • 10.Image classification algorithm
  • 11.Use USB camera
  • 12.Use MIPI camera
  • 13.Binocular camera depth algorithm
3.Basic development course
C language
  • 1.Camera image display
  • 2.Local save camera images
  • 3.Camera image encoding
  • 4.Video file decoding
  • 5.RTSP streaming decoding
  • 6.VPS scaling example
  • 7.Target detection algorithm-fcos
  • 8.Target detection algorithm-YOLOv5s
  • 9.Using CAN
Python
  • 0.ReadMe
  • 1.Using GPIO
  • 2.Using PWM
  • 3.Using Serial port
  • 4.Using I2C
  • 5.Using SPI
4.ROS expansion board
Python basic control
  • 0.Bind PCB port devices
  • 1.Install the Rosmaster driver library
  • 2.Buzzer whistle
  • 3.Control PWM servo
  • 4.RGB colorful light bar special effects display
  • 5.Control the forward and reverse rotation of the motor
  • 6.Control the movement of the robot
  • 7.Control Serial Servo
  • 8.Update firmware of expansion board
  • 9.Drive OLED
ROS2 robot control
  • 1.Function package usage process
  • 2.Robot information release
  • 3.Robot keyboard control
  • 4.Robot state estimation
  • 5.Robot calibration
  • 6.URDF model
5.T-MINI PLUS Lidar
  • 0.Preparation before use(Must read)
  • 1.Environment setup
  • 2.T-MINI PLUS LiDAR drive
  • 3.Handheld LiDAR mapping
6.AI VIEW Depth camera
AI VIEW Depth camera use
  • 1.AI VIEW Depth camera use
  • 2.Camera internal parameter calibration
  • 3.Color tracking
  • 4.KCF object tracking
Mediapipe functions
  • 1.Hand detection
  • 2.Attitude detection
  • 3.Overall inspection
  • 4.Facial detection
  • 5.Facial recognition
OpenCV series courses
  • 1.ROS+opencv application
  • 2.QR code creation and recognition
  • 3.AR vision
7.Offline AI model course
Offline-LLM-Text-Interaction
  • 0.AI-Large-Model-Image-Description
  • 1.AI-Large-Model-Environment-Deployment
  • 2.LLM-Conversation-Platform-Installation
  • 3.Meta-AI-Llama3.2-Model
  • 4.Alibaba-Cloud-Qwen3-Model
  • 5.Microsoft-Phi-4-mini-Model
  • 6.DeepSeek-DeepSeek-R1-Model
  • 7.Alibaba-Cloud-Qwen2.5vl-Vision-Multimodal-Model
  • 8.Google-Gemma3-Vision-Multimodal-Model
  • 9.Llava-Vision-Multimodal-Model
  • 10.MiniCPM-V-Vision-Multimodal-Model
  • 11.Multimodal-Text-to-Image-Application
  • 12.Multimodal-Video-Analysis-Application
  • 13.Multimodal-Visual-Understanding-Application
  • 14.Multimodal-Visual-Localization-Application
  • 15.Multimodal-Table-Scanning-Application
  • 16.Multimodal-Autonomous-Agent-Application
Offline-LLM-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-Analysis-Application
  • 7.Multimodal-Visual-Localization-Application
  • 8.Multimodal-Table-Scanning-Application
  • 9.Multimodal-Autonomous-Agent-Application
  • 10.AI-Large-Model-Offline-Voice-Assistant
8.Online AI model course
Online-LLM-Text-Interaction
  • 1.OpenRouter-Large-Model-API-Aggregation-Platform
  • 2.Multimodal-Visual-Understanding-Application
  • 3.Multimodal-Visual-Localization-Application
  • 4.Multimodal-Table-Scanning-Application
  • 5.Multimodal-Autonomous-Agent-Application
Online-LLM-Voice-Interaction
  • 0.Voice-Interaction-Hardware-Connection-Must-Read
  • 1.Online-Speech-to-Text-ASR
  • 2.Online-Text-to-Speech-TTS
  • 3.AI-Large-Model-Voice-Interaction
  • 4.Multimodal-Visual-Voice-Interaction
  • 5.Multimodal-Visual-Localization-Application
  • 6.Multimodal-Table-Scanning-Application
  • 7.Multimodal-Autonomous-Agent-Application
  • 8.AI-Large-Model-Online-Voice-Assistant
9.YOLO26 tutorials
  • 01.YOLO environment construction
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented bounding box object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training conversion
  • 11.Model prediction
10.OpenClaw Deployment and Basic Usagenew
  • 01.OpenClaw Quick Start
  • 02.OpenClaw Deployment
  • 03.OpenClaw WhatsApp Plugin Application
  • 04.OpenClaw WebChat Interaction
  • 05.OpenClaw TUI Interaction
  • 06.OpenClaw Tools Introduction
  • 07.OpenClawGate Gateway User Manual
  • 08.OpenClaw Features Overview
  • 09.OpenClawClawHub Introduction (Skill Installation)
  • 10.OpenClaw Application - File Management
  • 11.OpenClaw Application - Camera
  • 12.OpenClaw Application - Browser Control
  • 13.OpenClaw Application - Script Execution
  • 14.OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 15.OpenClaw Application - Dedicated AI Assistant
  • 16.OpenClaw Web Search Capability Configuration
11.OpenClaw Advanced Developmentnew
1.Preparation Before Use
  • 01. Peripheral Hardware Configuration
  • 02. OpenClaw API-KEY Configuration
  • 03. OpenClaw Model Switching
  • 04. OpenClaw Prompts
  • 05. AI Voice Interaction Configuration
  • 06. Three Dialogue Configuration Tests
2.OpenClaw AI Programming Peripheral Control
  • 1. Servo Control
  • 2. RGB Strip
  • 3. OLED Display
  • 4. Temperature and Humidity Sensor
  • 5. Camera Application
  • 6. AI Script Peripheral Control
3.OpenClaw Peripheral Integration Applications
  • 1. Plant Care Assistant
  • 2. AI Calorie Estimation
  • 3. AI Rock Paper Scissors Game
  • 4. AI Pet
  • 5. AI Weather Station
  • 6. Temperature and Humidity Dashboard
  • 7. Scheduled Tasks
12.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
  • System_File
  • Code
  • Tools
Download ZIP

Welcome to RDK X5 Board repository

5.ROS2 function package

5. ROS2 Function Packages

1. Introduction to Function Packages

Each robot may have many functions, such as motion control, visual perception, and autonomous navigation. While it's possible to lump the source code for all of these functions together, when we want to share some of these functions with others, we often find the code all mixed together, making it difficult to separate them.

Function packages work in this way. We separate the code for different functions into separate packages, minimizing the coupling between them. When sharing with others in the ROS community, we only need to explain how to use the package, and others can quickly start using it.

Thus, the function package mechanism is one of the key methods for increasing software reuse in ROS.

2. Creating Function Packages

How do I create a function package in ROS2? We can use this command:

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ros2 pkg create <package_name> --build-type <build-type> --dependencies <dependencies> --node-name <node-name>

In the ros2 command:

  • pkg: Indicates the functions associated with the package;
  • create: Creates the package;
  • package_name: Required: The name of the new package;
  • build-type: Required: Indicates whether the newly created package is C++ or Python. If using C++ or C, use ament_cmake; if using Python, use ament_python;
  • dependencies: Optional: Indicates the package's dependencies. A C++ package must include rclcpp; a Python package must include rclpy, as well as other required dependencies;
  • node-name: Optional: The name of the executable program. The corresponding source files and configuration files will be automatically generated.

For example, to create C++ and Python versions of the package in the terminal:

  • Switch to the src directory of the workspace.
  • Replace "workspace" with your actual folder path.
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cd workspace/src
  • Create a C++ package example
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ros2 pkg create pkg_helloworld_cpp --build-type ament_cmake --dependencies rclcpp --node-name helloworld
  • Create a Python package example
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ros2 pkg create pkg_helloworld_py --build-type ament_python --dependencies rclpy --node-name helloworld

3. Compile the package

In the created package, we can continue writing code. We will then need to compile and configure environment variables for proper operation:

  • Switch to the workspace directory
  • Compile all packages
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colcon build
  • Compile a specific package
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colcon build --packages-select pkg1 pkg2

4. Complete Workspace Structure with Feature Packages

The directory structure of a ROS2 workspace is as follows:

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WorkSpace --- Customized workspace.
    |--- build: Directory for storing intermediate files. A separate subdirectory is created within this directory for each feature package.
    |--- install: Installation directory. A separate subdirectory is created within this directory for each feature package.
    |--- log: Log directory for storing log files.
    |--- src: Directory for storing feature package source code.
        |-- C++ Feature Package
            |-- package.xml: Package information, such as package name, version, author, and dependencies.
            |-- CMakeLists.txt: Configuration of compilation rules, such as source files, dependencies, and target files.
            |-- src: Directory for C++ source files.
            |-- include: Directory for header files.
            |-- msg: Directory for message interface files.
            |-- srv: Directory for service interface files.
            |-- action: Action interface file directory.
        |-- Python package
            |-- package.xml: Package information, such as package name, version, author, and dependencies.
            |-- setup.py: Similar to the CMakeLists.txt file for a C++ package.
            |-- setup.cfg: Basic package configuration file.
            |-- resource: Resource directory.
            |-- test: Stores test-related files.
            |-- Package directory with the same name: Python source file directory.

In addition, both Python and C++ packages can customize directories related to configuration files.

xxxxxxxxxx
|-- C++ or Python package
    |-- launch: Stores launch files.
    |-- rviz: Stores rviz2 configuration files.
    |-- urdf: Stores robot model files.
    |-- params: Stores parameter files.
    |-- world: Stores simulation environment-related files.
    |-- map: Stores map files required for navigation.
    |-- ......

These directories can also be defined with other names, or additional directories can be created as needed.

 

ROS2 workspace
ROS2 node

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