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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

1.AI VIEW Depth camera use

1、Environment Setup

This section uses Ubuntu 22.04 + ROS Humble as an example to explain how to set up and use a camera in a ROS 2 environment.

1、Install Dependencies

Open a terminal and run:

sudo apt install libgflags-dev nlohmann-json3-dev libgoogle-glog-dev ros-humble-image-transport ros-humble-image-publisher

Install the libuvc library:

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git clone https://github.com/libuvc/libuvc.git
cd libuvc
mkdir build && cd build
cmake .. && make -j4
sudo make install
sudo ldconfig # Refreshing the link library

2、 Compile

1)Create a Workspace

Using orbbec_ws as the workspace name under the ~ home directory:

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mkdir orbbec_ws
cd orbbec_ws
mkdir src

2)Copy the Package into the Workspace

Extract the source archive, then copy the folders (packages) from the src directory into ~/orbbec_ws/src.

3)Compile

Open a terminal and run:

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cd ~/orbbec_ws
colcon build

4)Add Environment Variables

Open a terminal and run:

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echo "source ~/orbbec_ws/install/setup.bash" >> ~/.bashrc

3、Install udev Rules

Open a terminal and run:

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cd orbbec_ws/src/OrbbecSDK_ROS/orbbec_camera/scripts/
sudo sh install_udev_rules.sh

To verify that the rules file was loaded successfully and the camera is bound, run:

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#gemini max
ll /dev/gemini

image-20241015152351856

If the output matches the screenshot above, the setup was successful.

4、Launch the Camera and View Images

Open a terminal and run:

x
#gemini max camera start
ros2 launch astra_camera gemini.launch.xml

image-20240524173207093

To view the available topics, run:

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ros2 topic list

image-20240524173232765

To view the camera images using the rqt_image_view tool, run:

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ros2 run rqt_image_view rqt_image_view

Color image

image-20230619183120052

Depth image

image-20230619183155985

Infrared (IR) image

image-20230619183257816

In the rqt window, select the desired topic from the drop-down in the top-left corner to display.

5、Launch the Camera and View Point Cloud

Open a terminal and run:

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ros2 launch astra_camera gemini.launch.xml

To visualize the point cloud data published by the camera, open RViz2:

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rviz2

image-20230619183755016

Once RViz2 is open, configure the point cloud visualization settings as shown in the screenshots above.

image-20230619183940644

Handheld LiDAR mapping
Camera internal parameter calibration

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