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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

6. AI Script Peripheral Control

OpenClaw AI Script Peripheral Control Tutorial

Before starting, please complete [01-Peripheral Hardware Configuration], [02-OpenClaw API-KEY Configuration], [03-OpenClaw Model Switching], [04-AI Voice Interaction Configuration], and [05-Three Dialogue Configuration Tests] in the Preparation Before Use directory. If you are only using TUI/WhatsApp, you can skip 04. This article assumes the basic environment is ready and only covers the "having AI generate independently runnable scripts" part.

1. Tutorial Objectives

This article demonstrates that OpenClaw can not only directly control peripherals but also help you save control logic into script files through the approach of "natural language generation of hardware scripts". After completing this tutorial, readers will be able to:

  • Understand the basic approach to generating hardware control scripts with OpenClaw
  • Communicate with OpenClaw via WhatsApp, TUI, and voice commands
  • Generate four types of common scripts: RGB, servo, temperature and humidity, OLED

2. Hardware Preparation

  • OpenClaw main control board
  • Servo / RGB light strip / OLED / DHT temperature and humidity sensor
  • [Optional] AI voice module + speaker

Note:

  • This tutorial does not require connecting all peripherals at once
  • If you want to demonstrate which type of script, just connect the corresponding hardware first

3. Software Preparation

Code entry points used in this tutorial:

  • Script generation skill: /home/pi/.openclaw/workspace/skills/script-runner/SKILL.md
  • Script default save directory: /home/pi/Desktop/
  • Hardware command example directory: /home/pi/hardware_hal_demo/
  • Voice entry: /home/pi/voice_to_openclaw/src/main.py

The core of this capability is not "execute an immediate command" but having OpenClaw help you generate an independently runnable Python script. According to existing skill conventions:

  • When users say "generate script", "write a script", "save to desktop", it will preferentially use script-runner
  • Hardware scripts use openclaw_lib by default
  • Default serial port is /dev/ttyAMA0
  • Default baud rate is 115200
  • Scripts are usually saved to /home/pi/Desktop/

You can think of it as two usage methods:

  • Method 1: Generate script and run immediately
  • Method 2: Only generate script, save to desktop first, then modify or run again later

4. Testing Script Generation Capability

Before starting this tutorial, please complete an openclaw tui basic conversation self-check first; if you haven't done this yet, see [05-Three Dialogue Configuration Tests]. After confirming OpenClaw can respond normally, proceed with the script generation-specific test.

Enter TUI by typing the following in the terminal:

openclaw tui

image-20260428185733322

It is recommended to start with the simplest script requirements, for example:

  • Help me write a script that makes RGB red lights flash 5 times, save to desktop and run
  • Generate a script that reads temperature and humidity, don't run it yet
  • Write a script that makes servo 1 swing back and forth between 0, 90, 180 degrees
  • Generate a script that displays "Hello OpenClaw" on OLED

5. Three Ways to Communicate with OpenClaw

MethodSuitable ScenarioAdvantagesSuggested Use
WhatsAppRemote requirement sending, classroom demonstrationCan directly describe "help me write what script"Used to demonstrate natural language generation capability
TUILocal debugging, verify generation resultsEasiest to see script generation and run returnsFirst choice for debugging solution
Voice CodeVoice interaction, complete AI experienceCan directly verbally describe script requirementsAs the complete demonstration solution

If you have the optional AI voice module + speaker, the TUI and WhatsApp conversations need to broadcast OpenClaw's replies. You can run the following program in the terminal. This is not needed for AI voice module conversations.

  • Modify the TTS enable parameter
xxxxxxxxxx
/home/pi/voice_to_openclaw/.env
xxxxxxxxxx
ENABLE_TTS=true  # This parameter controls whether to broadcast replies. After saving, run the program below in the terminal.
  • Terminal input
xxxxxxxxxx
cd ~/voice_to_openclaw
source .venv/bin/activate
python -m src.openclaw_session_tts

image-20260511200528817

5.1 WhatsApp Solution

For WhatsApp integration steps, please refer directly to [05-Three Dialogue Configuration Tests]. This section only includes dialogue examples suitable for the script generation tutorial.

You can converse directly, for example:

  • Generate a script that makes servo swing left and right for 10 seconds and run it

image-20260428185908964

image-20260428185931543

5.2 TUI Solution

If you have already completed the TUI self-check from chapter 0, simply type the following command in the terminal to continue the conversation:

xxxxxxxxxx
openclaw tui

Then you can directly input script requirements, for example:

  • Help me write a script that controls RGB to become blue breathing light and run it

image-20260428190028668

5.3 Voice Code Solution

xxxxxxxxxx
Requires optional AI voice interaction module + speaker

For voice module installation, environment configuration, and basic wake-up flow, please refer directly to [04-AI Voice Interaction Configuration]. After waking up, you can directly speak control content, for example:

  • Write a script that displays current temperature and humidity on the screen and run it

image-20260428190209055

6. Comprehensive Cases

Note: All demonstrations below use the openclaw tui method for conversation. You can also choose WhatsApp or voice to complete.

6.1 Case 1: RGB Flashing Script

Experiment Objective

Have OpenClaw generate a basic lighting script to verify the "script creation + peripheral execution" chain.

Effect Description

OpenClaw will organize your natural language requirements into a Python script. After the script is saved to the desktop, it can be run directly or kept for later modification.

Example Commands

  • Help me write a script that makes RGB red lights flash 5 times
  • Generate a blue breathing light script, save to desktop and run
  • Write a script that makes RGB do a rainbow light effect

6.2 Case 2: Servo Action Script

Experiment Objective

Generate a servo action script to solidify single conversation actions into repeatable programs.

Effect Description

This type of script is suitable for actions like "nodding", "head shaking", "swinging back and forth", "returning to center", and is also suitable for later expansion into classroom demonstrations or combined projects.

Example Commands

  • Write a script that makes servo 1 move back and forth between 0, 90, 180 degrees
  • Generate a servo nodding script
  • Help me write a script that makes four servos return to 90 degrees together

6.3 Case 3: Temperature and Humidity Reading Script

Experiment Objective

Generate a script that reads current temperature and humidity and outputs results.

Effect Description

This type of script is suitable for sensor self-check, data sampling, or subsequent log recording, and is also the most commonly used type of basic script when doing scheduled tasks later.

Example Commands

  • Generate a script that reads temperature and humidity, save to desktop
  • Help me write a script that prints current temperature and humidity
  • Write a script that reads DHT data once and runs it

6.4 Case 4: OLED Display Script

Experiment Objective

Generate a script that displays text or metric content on OLED.

Effect Description

This case is suitable for welcome pages, status pages, simple dashboards, and is also the foundation for later linking with capabilities like temperature and humidity and cameras.

Example Commands

  • Help me write a script that displays "Hello OpenClaw" on OLED
  • Generate a script that displays temperature and humidity on OLED
  • Write a script that displays a page of simple status information

6.5 Case 5: Combined Script

Experiment Objective

Have OpenClaw generate a comprehensive script containing multiple peripheral actions at once.

Effect Description

This type of script can chain "read sensor", "display on OLED", "control RGB", "drive servo", suitable for transitioning from single peripheral control to small project scripts.

Example Commands

  • Write a comprehensive script: read temperature and humidity and display on OLED
  • Generate a script: first light up green light, then make servo rotate to 90 degrees
  • Help me write a script: if temperature is too high, light up red light and prompt on OLED
Camera Application
Plant Care Assistant

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