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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

01. Peripheral Hardware Configuration

OpenClaw Peripheral Hardware Configuration

OpenClaw Peripheral Hardware Configuration1. Course Overview2. Hardware Configuration File Description2.1 Configuration File Location2.2 Current Configuration File Coverage2.3 Peripheral Wiring Diagrams3. DHT Hardware Testing3.1 Verification Method4. RGB Hardware Testing4.1 Verification Method5. Servo Hardware Testing5.1 Verification Method6. OpenClaw Firmware Serial Port Settings6.1 Current Default Values6.2 Modification Example6.3 Verification Method7. OLED Hardware Testing7.1 Current Default Values7.2 Scenarios Suitable for Modification7.3 Common Modification ItemsModify ResolutionModify I2C AddressModify Rotation Direction7.4 Verification Method8. Camera Hardware Testing8.1 Configuration8.2 Photo Verification Method8.3 Adjustable Parameter Description

1. Course Overview

This course will introduce the default configuration files related to hardware before using OpenClaw, focusing on how to modify underlying default parameters according to the actual situation of your peripherals and complete basic verification.

  • Use low-level commands to verify if modifications take effect

2. Hardware Configuration File Description

2.1 Configuration File Location

The current hardware default configuration file for OpenClaw is located at:

/home/sunrise/hardware_hal_demo/hardware_config.py

If you are following the accompanying tutorial and using the accompanying factory hardware with the default factory image, you usually do not need to modify it.

2.2 Current Configuration File Coverage

hardware_config.py currently mainly contains three types of default configurations:

  • OpenClaw firmware serial port default parameters

  • OLED default parameters

These default values are read by low-level command-line tools, such as:

  • rgb

  • oled

  • dht

It should be noted that:

  • DHT and RGB are driven directly through the OpenClaw expansion board firmware

  • OLED is driven through the motherboard's I2C pins

  • CSI camera requires checking hardware connections

2.3 Peripheral Wiring Diagrams

  • The OLED and temperature/humidity sensor do not require external connections; they are directly onboard on the OpenClaw expansion board.

  • Servo wiring diagram: as shown below, the S1 signal pin corresponds to yellow, red corresponds to 5V, and brown corresponds to GND.

    image-20260511185448511

     

  • RGB light strip has a fool-proof interface, see the image below.

    image-20260511185606216

  • Please power off before inserting. For the CSI camera, insert it straight down into the slot, with metal contacts facing the white side of the interface.

    image-20260527143732148

3. DHT Hardware Testing

Note: If you need to continuously read DHT via the Python driver library, it is recommended to read DHT data every two seconds for better stability.

3.1 Verification Method

xxxxxxxxxx
dht   # Get sensor data
dht_oled  # Display sensor data on OLED

Normal terminal output should show temperature and humidity data on the OLED.

image-20260527151508142

image-20260601095664837

4. RGB Hardware Testing

4.1 Verification Method

Run in terminal:

xxxxxxxxxx
rgb color --color red # All turn red
rgb effect --effect breathe --color blue --speed 5 # Blue breathing light

Normal terminal output should show the RGB lights displaying normally.

image-20260527151703808

image-20260601100886738

image-20260601100867354

Turn off the light strip:

xxxxxxxxxx
rgb off

image-20260527152029894

image-20260601101255342

5. Servo Hardware Testing

5.1 Verification Method

Control a single servo:

​x
servo call-tool Servo1 --action set_angle --angle 90  # Servo 1 turns to 90 degrees
servo call-tool Servo2 --action set_angle --angle 180  # Servo 2 turns to 180 degrees

# Servo1 is the servo to control
# 90 is the angle to turn to

image-20260527152242850

image-20260601095534621

image-20260601095013564

Synchronously control multiple servos:

Note: If you only have two servos, fill in the angles for two servos; the angles for the other two can be filled arbitrarily.

xxxxxxxxxx
# Four servos reach specified angles simultaneously
servo call-tool ServoAll --action set_all --angle1 90 --angle2 45 --angle3 135 --angle4 60 
# All servos return to center position
servo call-tool ServoAll --action set_all --angle1 90 --angle2 90 --angle3 90 --angle4 90

6. OpenClaw Firmware Serial Port Settings

6.1 Current Default Values

The current default serial port parameters for OpenClaw firmware are:

  • port="/dev/ttyS1"

  • baudrate=115200

Serial port naming may differ on other motherboards, for example, Jetson uses "/dev/ttyTHS1".

6.2 Modification Example

Edit the configuration file:

xxxxxxxxxx
nano /home/sunrise/hardware_hal_demo/hardware_config.py

Change RDK X5 to, for example:

xxxxxxxxxx
"port": "/dev/ttyS1",
"baudrate": 115200,

image-20260527152427766

6.3 Verification Method

After saving, it is recommended to first test with any low-level command for servo or RGB, for example:

xxxxxxxxxx
rgb color --color green 

Or:

xxxxxxxxxx
servo call-tool Servo1 --action center  # Servo 1 returns to center 90 degrees
# All servos return to center position
servo call-tool ServoAll --action set_all --angle1 90 --angle2 90 --angle3 90 --angle4 90

If the command returns normally and can control the peripheral correctly, it means the serial port link is available.

image-20260527152627499

7. OLED Hardware Testing

7.1 Current Default Values

Current OLED default parameters mainly include:

  • width=128

  • height=32

  • interface="i2c"

  • i2c_bus="5"

  • i2c_bus_candidates=[5]

  • i2c_address=0x3C

  • rotate=0

  • invert=False

  • contrast=255

7.2 Scenarios Suitable for Modification

It is recommended to modify OLED default values in the following situations:

  • You are using an OLED with a different resolution

  • I2C address is not 0x3C

  • Screen orientation needs to be flipped

7.3 Common Modification Items

Modify Resolution

For example, change:

xxxxxxxxxx
"width": 128,
"height": 32,

To:

xxxxxxxxxx
"width": 128,
"height": 64,

Modify I2C Address

For example, change:

xxxxxxxxxx
"i2c_address": 0x3C,

To:

xxxxxxxxxx
"i2c_address": 0x3D,

Modify Rotation Direction

For example, change:

xxxxxxxxxx
"rotate": 0,

To:

xxxxxxxxxx
"rotate": 180,

7.4 Verification Method

After saving, run in terminal:

xxxxxxxxxx
oled text --text 'Hello OpenClaw' 
oled clear 

If the OLED can display and clear normally, it means the configuration has taken effect.

image-20260527152951428

8. Camera Hardware Testing

8.1 Configuration

Prerequisite is to ensure the CSI camera is connected. The current CSI camera pipeline mainly works through the following two entry points:

xxxxxxxxxx
/home/sunrise/hardware_hal_demo/camera
/home/sunrise/.openclaw/workspace/skills/sunrise-vision/scripts/csi_snap

8.2 Photo Verification Method

Enter instructions in terminal to first directly test the photo pipeline:

xxxxxxxxxx
camera

image-20260527153031845

If the photo is successful, you will usually see output files in the following directory:

xxxxxxxxxx
~/.openclaw/media/csi-camera/

image-20260428111323882

If the photo fails, it is likely that the camera pipeline is stuck; unplug and reinsert the camera (perform this operation while powered off).

8.3 Adjustable Parameter Description

Although the camera is not currently configured in hardware_config.py, the camera command supports some photography parameters when called, such as:

  • --width

  • --height

  • --timeout-ms

  • --rotation

  • --hflip

  • --vflip

  • --camera

For example:

xxxxxxxxxx
camera --width 1280 --height 720 

image-20260527153259815

 

OpenClaw Web Search Capability Configuration
OpenClaw API-KEY Configuration

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