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Raspberry Pi 5📖
00.Quick Start (Must See)
  • 1.Quick Start (Must See)
  • 2.TF card expand capacity
  • 3.Raspberry Pi 5 - 1GB Version Must - See Before Use
01.Introduction to Raspberry PI 5
  • 1. Introduction to Raspberry PI 5
  • 2. Raspberry PI system installation and backup
  • 3. Powering the Raspberry PI 5
  • 4. Startup of Raspberry PI 5
  • 5. Installation and introduction of shell and active radiator
  • 6. GPIO and 40-pin pins
  • 7. Tips for using Raspberry PI 5
  • 8. Raspberry PI PCIe connector
  • 9. MIPI CSI DSI connector
  • 10. UART connector
  • 11. Real-time clock
  • 12. Power over Ethernet (PoE) connector
02.Introduction to common mirror systems
  • 1. Official Raspberry PI system
  • 2. Ubuntu
03.Basic settings of Raspberry Pi
  • 1. Update and upgrade operating system
  • 2.Introduction to raspi-config tool
  • 3.config.txt file description
  • 4.Network Configuration
  • 5.remote access
  • 6.Transfer files remotely
  • 7.Set display resolution and rotation
  • 8.Set screen to sleep
  • 9.Get real-time temperature of Raspberry Pi
  • 10.Play audio and video
  • 11.Using USB camera
  • 12.Using MIPI camera
04.Basic programming course
1. C language programming
  • 1. C language environment construction
  • 2. Print Hello World
2. Python programming
  • 1.Python usage
  • 2.Use APT to install Python packages
  • 3.Python virtual environment
  • 4.GPIO Zero
  • 5.Pin output high and low levels
  • 6.Pin reads high and low levels
  • 7.Pin output PWM
3.Jupyter lab programming
  • 1.Jupyter Lab environment construction
  • 2.Basic use of Jupyter Lab
  • 3.Jupyter Lab plug-in installation
  • 4.Basic use of Jupyter Widgets
05.Advanced AI course
5.Advanced AI gameplay
  • 1. Human pose estimation
  • 2. target detection
  • 3.yolov5
  • 4. Camera display
  • 5. QR code
  • 6. face detection
  • 7. Color recognition
2.Getting started with Open Source CV
  • 1. Introduction to Open Source CV
  • 2. Read and display Open Source CV images
  • 3. Open Source CV image writing
  • 4. Open Source CV image quality
  • 5.Open Source CV pixel operation
3.Open Source CV Geometric Transformations
  • 1. Image resizing
  • 2. Cut the image
  • 3. Image translation
  • 4. Image mirroring
  • 5. Affine transformation
  • 6. Rotate the image
  • 7. Perspective transformation
4.Text Picture Drawing Open Source CV image processing and drawing text line segments
  • 1、Grey Processing
  • 2、image binaryzation
  • 3、edge detection
  • 4、Line segment drawing
  • 5、Rectangle and circle drawing
  • 6、Text image drawing
1.Open Source CV environment setup
  • Open Source CV environment setup
6.YOLOv11 development
  • 1. YOLOv11 environment construction
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model conversion
  • 9. Dataset Annotation
  • 10. Model training_conversion
  • 11. Model prediction
7.YOLO26 development
  • 01.YOLO26 environment
  • 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
06.Mediapipe course
  • 1. Face special effects
  • 2. Face detection
  • 3. Three-dimensional object recognition
  • 4. Paintbrush
  • 5. Finger control
  • 6. Gesture recognition
07.Docker Tutorial
  • 1.Overview and installation
  • 2.Common commands
  • 3.Understand and publish images
  • 4.Hardware interaction data processing
  • 5.Enter docker container
  • 6.Update docker images
  • 7. docker container to install ROS using accessories
08.ROS1 advanced tutorial
1.ROS1 basic course
  • 1.ROS introduction
  • 2.ROS installation
  • 3.ROS common command tools
  • 4.ROS workspace
  • 5.ROS function package
  • 6.ROS node
  • 7.ROS topic publisher
  • 8.ROS topic subscribers
  • 9.ROS service client
  • 10.ROS service server
  • 11.ROS action client
  • 12.ROS action server
  • 13.ROS custom message reception
  • 14.ROS-launch file
  • 15.ROS-TF transformation
  • 16.ROS parameter service
  • 17.ROS-rviz use
  • 18.ROS-rqt tool usage
  • 19.Topic message recording and playback
  • 20.urdf model introduction
  • 21.gazebo introduction
  • 22.ROS distributed communication
2.ROS1 vision application
  • 0.Precautions
  • 1.AR vision
  • 2.AR QR code
  • 3.ROS+Opencv basics
  • 4.Face recognition
  • 5.harris corner detection
  • 6.Target tracking algorithm
  • 7.Contour moment
  • 8.Polygon outline
  • 9.Discrete fourier transform algorithm
  • 10.Edge detection algorithm
  • 11.Face detection algorithm
  • 12.Optical flow detection algorithm
  • 13.Contour detection
  • 14.General contour detection
  • 15.Feature point tracking
  • 16.HLS color filtering
  • 17.Hough circle detection
  • 18.Hough linear detection
  • 19.HSV color filtering
  • 20.LK optical flow algorithm
  • 21.detection algorithm
  • 22.Phase dependent displacement detection
  • 23.Image pyramid sampling algorithm
  • 24.RGB color filtering
  • 25.Clear background detection algorithm
  • 26.Simplified optical flow algorithm
  • 27.Simple filter
  • 28.Threshold image processing
  • 29.Watershed segmentation algorithm
09.ROS2 advanced tutorial
1.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
2.ROS2 vision application
  • 0.Precautions
  • 1.Opencv basic course
  • 2.ROS+opencv application
  • 3.QR code creation and recognition
  • 4.AR vision
  • 5.Interesting gameplay of mediapipe
10.Offline AI model coursenew
Offline large model (Text Interaction)
  • 0. AI large model image description
  • 1. Deployment of large AI model environments
  • 2. Switch Chinese input method
  • 3. Installation of large model dialogue platform
  • 4. Meta AI Llama 3.2 model
  • 5. Alibaba Cloud Qwen3 Model
  • 6. Microsoft Phi-4-mini model
  • 7. DeepSeek DeepSeek-R1 model
  • 8. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 9. Google Gemma3 Visual Multimodal Large Model
  • 10. Llava Visual Multimodal Large Model
  • 11.MiniCPM-V Visual Multimodal Large Model
  • 12. Multimodal Visual Understanding Applications
  • 13. Multimodal Text-Based Image Application
  • 14. Multimodal Video Analysis Application
  • 15. Multimodal visual positioning applications
  • 16. Multimodal table scanning application
  • 17. Multimodal Autonomous Agent Application
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 and voice interaction
  • 5. Multimodal Text-Based Image Application
  • 6. Multimodal Video Analysis Application
  • 7. Multimodal visual positioning applications
  • 8. Multimodal table scanning application
  • 9. Multimodal Autonomous Agent Applications
  • 10. AI large model offline voice assistant
11.Online AI model coursenew
Online large model (text interaction)
  • 1.OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal Visual Understanding Applications
  • 3. Multimodal visual positioning applications
  • 4. Multimodal table scanning application
  • 5. Multimodal Autonomous Agent Applications
Online large model (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 and voice interaction
  • 5. Multimodal visual positioning applications
  • 6. Multimodal table scanning application
  • 7. Multimodal Autonomous Agent Applications
  • 8. AI large model online voice assistant
12.OpenClaw Deployment and Basic Usagenew
  • 01. OpenClaw Deployment
  • 02. OpenClaw WhatsApp Plugin Application
  • 03. OpenClaw WebChat Interaction
  • 04. OpenClaw TUI Interaction
  • 05. OpenClaw Tools Introduction
  • 06. OpenClawGate Gateway User Manual
  • 07. OpenClaw Features Overview
  • 08. OpenClawHub Introduction (Skill Installation)
  • 09. 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
13.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. 3D 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
Download
  • SystemFile
  • Code
  • SoftWare
  • 3D_Model_File
  • GuideManual
Download ZIP

Welcome to Raspberry Pi 5 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 Coverage3. 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 Check Ports8.3 Photo Capture Verification Method8.4 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 the underlying default parameters according to your actual peripheral situation and complete basic verification.

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

2. Hardware Configuration File Description

2.1 Configuration File Location

OpenClaw's current hardware default configuration file is located at:

/home/pi/hardware_hal_demo/hardware_config.py

The default uses the factory image. If you are only following the tutorial and using the factory hardware, you usually don't need to modify it.

2.2 Current Configuration File Coverage

hardware_config.py currently mainly includes 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

Important notes:

  • DHT and RGB are driven directly through the OpenClaw expansion board firmware
  • OLED is driven through the motherboard's I2C pins
  • CSI camera needs to check hardware connection

3. DHT Hardware Testing

Note: If you need to continuously read DHT through the Python driver library, it is recommended to read DHT data at a two-second interval, as DHT sensors are more suitable for 2s sampling

3.1 Verification Method

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

Normal terminal display will show temperature and humidity data on OLED

image-20260428110308142

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 display will show RGB lights displaying normally

image-20260428110503808

Turn off the light strip

xxxxxxxxxx
rgb off

image-20260506105329894

5. Servo Hardware Testing

5.1 Verification Method

Control single servo:

​x
servo call-tool Servo1 --action set_angle --angle 90  #Servo 1 rotates to 90 degrees
servo call-tool Servo2 --action set_angle --angle 180  #Servo 2 rotates to 90 degrees
​
#Servo1 is the servo to control
#90 is the angle to rotate to

image-20260506105642850

Synchronously control multiple servos:

Note: If there are only two servos, fill in the angles for both servos, the angles for the other two servos can be arbitrary

xxxxxxxxxx
# Four servos simultaneously reach specified angles
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

Current OpenClaw firmware serial port default parameters are:

  • port="/dev/ttyAMA0"
  • baudrate=115200

Other motherboards' pin serials may not be named this way. For example, Jetson's is "/dev/ttyTHS1"

6.2 Modification Example

Edit the configuration file:

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

Change Raspberry Pi to, for example:

xxxxxxxxxx
"port": "/dev/ttyAMA0",
"baudrate": 115200,

image-20260506110127766

6.3 Verification Method

After saving, it is recommended to first test with either servo or RGB low-level commands, 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 commands can return normally and peripherals can be controlled normally, the serial link is usable.

image-20260428111727499

7. OLED Hardware Testing

7.1 Current Default Values

Current OLED default parameters mainly include:

  • width=128
  • height=32
  • interface="i2c"
  • i2c_bus="auto"
  • i2c_bus_candidates=[1, 0, 7, 8]
  • 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 different resolution
  • I2C address is not 0x3C
  • Screen orientation needs to be flipped

7.3 Common Modification Items

Modify Resolution

For example, change from:

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

To:

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

Modify I2C Address

For example, change from:

xxxxxxxxxx
"i2c_address": 0x3C,

To:

xxxxxxxxxx
"i2c_address": 0x3D,

Modify Rotation Direction

For example, change from:

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 OLED can display normally and clear the screen, the configuration has taken effect.

image-20260428110951428

8. Camera Hardware Testing

8.1 Configuration

The premise is ensuring a CSI camera is connected. The current CSI camera chain mainly works through the following two entry points:

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

8.2 Check Ports

Input in terminal:

xxxxxxxxxx
ls /dev/video*

Normally you can see video0 and video1 devices.

image-20260428111155499

8.3 Photo Capture Verification Method

Input in terminal and directly test the photo capture chain:

xxxxxxxxxx
csi_snap snap

image-20260428111231845

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

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

image-20260428111323882

8.4 Adjustable Parameter Description

Although camera is currently not configured in hardware_config.py, csi_snap supports some photo parameters when called, such as:

  • --width
  • --height
  • --timeout-ms
  • --rotation
  • --hflip
  • --vflip
  • --camera

For example:

xxxxxxxxxx
csi_snap snap --width 1280 --height 720

image-20260428111459815

OpenClaw Application - Dedicated AI Assistant
OpenClaw API-KEY Configuration

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