yahboom
HomeLearn
Solution
Blog
Online Store
About Us
EN/中文
Jetson Orin NX SUPER📖
01.Get started
  • 01. Learning route
  • 02. Get started quickly
  • 03. System Update Notes
  • 04.Disabling automatic updates and troubleshooting issues
02.Jetson basic course
  • 01.Jetson board introduction
  • 02.Write Jetson original system
  • 03.Installing Jetson environment
  • 04.Backup SSD system
  • 05.Restore initial image system
  • 06.Upgrade to SUPER version
  • 07.Write SUPER boot
  • 08.SSD expansion
  • 09.Jetpack old system upgraded to Yahboom SUPER factory system
  • 10.Write the system onto your own solid-state drive
03.Basic setting course
  • 01.Basic knowledge
  • 02.Network configuration
  • 03.SSH remote login
  • 04.VNC remote control
  • 05.Remote file transfer
  • 06.Jtop tool
  • 07.Exchange space expansion
  • 08.Use VSCode
  • 09.Use VMware
04.GPIO control course
  • 01.GPIO description
  • 02.GPIO library installation
  • 03.GPIO reading
  • 04.GPIO output
  • 05.Serial communication
  • 06.I2C communication
05.Vision basic course
  • 01.CSI camera preview
  • 02.USB camera preview
  • 03.Use Jupyter Lab
  • 04.Use JetCam
06.OpenCV basic course
  • 01.Image reading
  • 02.Image saving
  • 03.Image modification
  • 04.Image scaling
  • 05.Image cropping
  • 06.Image translation
  • 07.Image mirroring
  • 08.Image grayscale conversion
  • 09.Image binarization
  • 10.Image edge detection
  • 11.Add line segments
  • 12.Add rectangles
  • 13.Add circular shape
  • 14.Add ellipses
  • 15.Add polygons
  • 16.Add Text
  • 17.Preview USB camera image
  • 18.Preview CSI camera image
07.Vision advanced course
01.Environment construction
  • 01.TensorFlow
  • 02.PyTorch
  • 03.Torchvision
02.DeepStream development
  • 01.DeepStream environment
  • 02.Four types of detection(traffic)
03.YOLO11 development
  • 01.YOLO environment construction
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training conversion
  • 11.Model prediction
04.Mediapipe development
  • 01.Mediapipe environment
  • 02.Hand detection
  • 03.Face detection
  • 04.Face effects
  • 05.3D object recognition
  • 06.Virtual brush
  • 07.Gesture recognition
  • 08.Finger control
  • 09.Posture estimation
  • 10.Face mask
  • 11.Overall detection
  • 12.Green scene removal(Human)
05.QR code recognition
  • 01.QR code recognition
06.YOLO26 development
  • 01.YOLO environment constructionnew
  • 02.CLI usenew
  • 03.Object detectionnew
  • 04.Instance segmentationnew
  • 05.Pose estimationnew
  • 06.Image classificationnew
  • 07.Oriented object detectionnew
  • 08.Model conversionnew
  • 09.Dataset annotationnew
  • 10.Model training conversionnew
  • 11.Model predictionnew
08.Docker basic course
  • 01.Docker introduction
  • 02.Docker installation
  • 03.Docker command
  • 04.Docker usage
  • 05.Docker interaction
09.ROS1-Melodic
01.ROS1 basic course
  • 01. Introduction to ROS
  • 02. Project file structure
  • 03. Common commands and tools
  • 04. Publisher
  • 05. Subscribers
  • 06. Customize topic messages and use
  • 07. Client
  • 08. Server
  • 09. Customize service messages and usage
  • 10. TF release and monitoring
02.ROS1 vision course
  • 00.Must read before running
  • 01.Camera preview
  • 02.QR code
  • 03.Human posture estimation
  • 04.Target detection
  • 05.AR vision
  • 06.Opencv application
  • 07.ROS+Opencv basics
  • 08.Mediapipe development
10.ROS2-Humble
01.ROS2 basic course
  • 01.Introduction to ROS2
  • 02.ROS2 install Humble
  • 03.ROS2 development environment
  • 04.ROS2 workspace
  • 05.ROS2 function package
  • 06.ROS2 node
  • 07.ROS2 topic communication
  • 08.ROS2 service communication
  • 09.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
02.ROS2 vision course
  • 01.Camera preview (USB)
  • 02.Camera preview (CSI)
  • 03.Camera calibration (USB)
  • 04.Camera calibration (CSI)
  • 05.AR vision (USB)
  • 06.AR vision (CSI)
11.Offline AI model coursenew
Offline large model (Text Interaction)
  • 1.AI large model environment deployment
  • 2.Install large model dialogue platform
  • 3.Meta Al Llama3.2 model
  • 4.Alibaba Cloud Qwen3 model
  • 5.Microsoft Phi-4-mini model
  • 6.DeepSeek DeepSeek-R1 model
  • 7.Alibaba Cloud Qwen2.5v visual multimodal large model
  • 8.Google Gemma3 visual multimodal large model
  • 9.Lava visual multimodal large model
  • 10.MiniCPM-V visual multimodal large model
  • 11.Multimodal visual understand application
  • 12.Multimodal text image application
  • 13.Multimodal video analysis application
  • 14.Multi module visual position application
  • 15.Multimodal table scanning application
  • 16.Multimodal autonomous agent application
Offline large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Offline speech to text (ASR)
  • 2.Offline text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multimodal text and graphics application
  • 6.Multimodal video analysis application
  • 7.Multi module visual position application
  • 8.Multimodal table scanning application
  • 9.Multimodal autonomous proxy application
  • 10.AI large model offline voice assistant
12.Online AI model coursenew
Online large model (Text Interaction)
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal visual understand application
  • 3.Multimodal visual localization application
  • 4.Multimodal table scanning application
  • 5.Multimodal autonomous proxy application
Online large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Online speech to text (ASR)
  • 2.Online text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multi module visual position application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model online voice assistant
13.NVIDIA lsaac ROS coursenew
  • 1.Build lsaac ROS environment
  • 2.Deep segmentation
  • 3.DNN stereoscopic depth
  • 4.Free space segmentation
  • 5.Image distortion processing
  • 6.Image segmentation
  • 7.3D scene reconstruction and mapping
  • 8.Object detection
  • 9.3D attitude estimation
  • 10.Visual SLAM
14.OpenClaw Deployment and Basic Usagenew
  • 01.OpenClaw Quick Start on Jetson Platform
  • 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.OpenClawHub 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
15.OpenClaw Advanced Developmentnew
1.Preparation Before Use
  • 1. Peripheral Hardware Configuration
  • 2. OpenClaw API Key Configuration
  • 3. OpenClaw Model Switching
  • 4. OpenClaw Prompts
  • 5. AI Voice Interaction Configuration
  • 6. 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
Download
  • System_File
  • VM_File
  • 3D_Model_File
  • Data_Sheet_File
  • Software_Tools
  • Code
  • Instruction_Manual
  • ROS2_Basic_VM
Download ZIP

Welcome to Jetson Orin NX SUPER repository

当製品の日本語版マニュアル資料は、こちらからご取得ください。

1. Peripheral Hardware Configuration

OpenClaw Peripheral Hardware Configuration

OpenClaw Peripheral Hardware Configuration1. Course Overview2. Hardware Default Configuration File Description2.1 Configuration File Location2.2 Current Configuration File Coverage3. DHT Current Configuration Features3.1 Verification Method4. RGB Default Configuration4.1 Verification Method5. OpenClaw Firmware Serial Port Default Configuration (Servo Verification)5.1 Current Default Values5.2 Modification Example5.3 Verification Method6. OLED Default Configuration6.1 Current Default Values6.2 Scenarios Suitable for Modification6.3 Common ModificationsChanging ResolutionChanging I2C AddressChanging Rotation Direction6.4 Verification Method7. Camera Hardware Configuration7.1 Configuration7.2 Checking Ports7.3 Photo Verification Method

1. Course Overview

This course introduces the default hardware-related configuration files used before operating OpenClaw, with a focus on how to modify the underlying default parameters based on the actual peripherals you have, and complete basic verification.

  • Use underlying commands to verify whether modifications have taken effect

2. Hardware Default Configuration File Description

2.1 Configuration File Location

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

/home/jetson/hardware_hal_demo/hardware_config.py

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

2.2 Current Configuration File Coverage

hardware_config.py mainly contains three types of default configurations:

  • OpenClaw firmware serial port default parameters
  • OLED default parameters
  • CSI camera or USB camera

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

  • rgb
  • oled
  • openclaw_adapter
  • CAMERA_DEFAULTS

Please note:

  • DHT and RGB are currently driven directly by the OpenClaw firmware
  • OLED is driven by the motherboard's I2C pins
  • CSI camera/USB camera requires checking the hardware connection

3. DHT Current Configuration Features

3.1 Verification Method

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

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

image-20260529184529580

4. RGB Default Configuration

4.1 Verification Method

After saving, run the following in the terminal:

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

Normal terminal output should show the RGB lights displaying correctly.

image-20260529184554838

5. OpenClaw Firmware Serial Port Default Configuration (Servo Verification)

5.1 Current Default Values

The current OpenClaw firmware serial port default parameters are:

  • port="/dev/ttyTHS1"
  • baudrate=115200

5.2 Modification Example

Edit the configuration file:

xxxxxxxxxx
/home/jetson/hardware_hal_demo/hardware_config.py

For Jetson Orin NX, change the values as follows:

xxxxxxxxxx
"port": "/dev/ttyTHS1",
"baudrate": 115200,

5.3 Verification Method

After saving, we recommend first testing with a servo or RGB using any underlying command, for example:

xxxxxxxxxx
rgb color --color green 

Or:

xxxxxxxxxx
servo call-tool Servo1 --action center  #Servo 1 centers to 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 commands execute successfully and control the peripherals properly, the serial port link is working.

image-20260529184714831

6. OLED Default Configuration

6.1 Current Default Values

The 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

6.2 Scenarios Suitable for Modification

It is recommended to modify the OLED defaults in the following situations:

  • You are using an OLED with a different resolution
  • The I2C address is not 0x3C
  • The screen orientation needs to be flipped

6.3 Common Modifications

Changing Resolution

For example, change:

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

To:

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

Changing I2C Address

For example, change:

xxxxxxxxxx
"i2c_address": 0x3C,

To:

xxxxxxxxxx
"i2c_address": 0x3D,

Changing Rotation Direction

For example, change:

xxxxxxxxxx
"rotate": 0,

To:

xxxxxxxxxx
"rotate": 180,

6.4 Verification Method

After saving, run the following in the terminal:

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

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

image-20260529184745601

7. Camera Hardware Configuration

7.1 Configuration

Prerequisite: ensure that a CSI camera is connected. The current CSI camera link works mainly through the following two entry points:

If using a USB camera, you can modify the configuration in this file:

xxxxxxxxxx
/home/jetson/hardware_hal_demo/hardware_config.py
xxxxxxxxxx
# Camera default configuration
# backend: "csi" uses Jetson CSI camera; "usb" uses USB camera
CAMERA_DEFAULTS = {
    "backend": "usb",
    "usb_device": "/dev/video0",
    "usb_format": "auto",
    "width": 1280,
    "height": 720,
    "framerate": 30,
    "flip_method": 2,
    "sensor_id": 0,
}

Camera CLI command path:

xxxxxxxxxx
/home/jetson/hardware_hal_demo/cli/seewhat

7.2 Checking Ports

Enter in the terminal:

xxxxxxxxxx
ls /dev/video*

Normally, a CSI camera should show one device, video0, and a USB camera should show video0 and video1 devices.

image-20260529184928043

7.3 Photo Verification Method

Enter the following command in the terminal to test the photo capture:

xxxxxxxxxx
seewhat call-tool SeeWhat

image-20260529185011535

If the photo is captured successfully, you should see the output file in the following directory:

xxxxxxxxxx
/home/jetson/.openclaw/workspace/photos/latest.jpg

image-20260529185030327

OpenClaw Web Search Capability Configuration
OpenClaw API Key Configuration

COMPANY

  • About us
  • Team Style
  • Blog

LEARNING & EXPLORATION

  • Tutorials
  • Edge AI hardware
  • Educational robots
  • Embedded intelligent hardware

WHERE TO BUY

  • Yahboom Online Store
  • Amazon
  • Alibaba
  • AliExpress
  • Mercado

TECHNOLOGY SUPPORT

  • Email: support@yahboom.com

BE A DISTRIBUTOR

  • Email: sales@yahboom.com
QR Code

Copyright © 2017-2026 Yahboom. All Rights Reserved.

EN/中文