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Jetson AGX Orin📖
01.Get started
  • 01.Learning Route
  • 02.Getting Started Quickly
02.Jetson basic course
  • 01.Jetson board introduction
  • 02.Flash new system to the onboard eMMC
  • 03.Flash new system to an NVMe SSD
  • 04.Install Jetpack environment
  • 05.Backup SSD system
  • 06.Restore factory image system
  • 07.SSD expansion
  • 08.Solid State Drive Speed Test
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
  • 10. Change screen resolution
  • 11. Virtual Desktop
  • 12. Set root user password
  • 13. Configure sudo passwordless operation
  • 14. Managing custom services
  • 15. View system version information
04.GPIO control course
  • 01.GPIO description
  • 02.GPIO library installation
  • 03.GPIO reading
  • 04.GPIO output
  • 05.Serial communication
  • 06.I2C communication
05.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
06.Vision basic course
  • 01.USB camera preview
  • 02.Use Jupyter Lab
  • 03.Use JetCam
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.Barcode Recognition
  • 02.QR Code Recognition
  • 03.Machine Code Recognition
  • 04.Handwritten Digit Recognition
06.YOLO26 development
  • 01.YOLO Environment Setupnew
  • 02.CLI Usagenew
  • 03.Object Detectionnew
  • 04.Instance Segmentationnew
  • 05.Pose Estimationnew
  • 06.Image Classificationnew
  • 07.Oriented Bounding Boxes 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.ROS2-Humble
01.ROS2 basic course
  • 3.ROS2 development environment
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 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
02.ROS2 vision course
  • 01.Camera preview (USB)
  • 02.Camera calibration (USB)
  • 03.AR vision (USB)
10.Offline AI model course
Offline large model (Text Interaction)
  • 10.AI large model offline voice assistant
  • 1.Al 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
11.Online AI model course
Online large model (Text Interaction)
  • 8.AI large model offline voice assistant
  • 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
12.Offline Generative AI Applications
  • 01.Children's Storytelling Session
  • 02.Cooking Assistant
  • 03.Homework tutor
  • 04.Image to animation
13.OpenClaw Advanced Development
  • 00.OpenClaw Quick Start on Jetson Platform
  • 01.OpenClaw Installation
  • 02.OpenClaw Online Platform Deployment
  • 03.OpenClaw Local Model Deployment
  • 04.OpenClaw TUI Interaction
  • 05.OpenClaw WebChat Interaction
  • 06.OpenClaw Tools Introduction
  • 07.OpenClawGate Gateway User Manual
  • 08.OpenClaw Features Overview
  • 09.OpenClawClawHub Introduction (Skill Installation)
  • 10. OpenClaw Switching Models
  • 11.OpenClaw Application - File Management
  • 12.OpenClaw Application - Camera
  • 13.OpenClaw Application - Browser Control
  • 14.OpenClaw Application - Script Execution
  • 15.OpenClaw Application - AI Programming
  • 16.OpenClaw Application - Dedicated AI Assistant
  • 17.OpenClaw WhatsApp Plugin Application
Download
  • System_File
  • VM_File
  • Code
  • Tools
Download ZIP

Welcome to Jetson AGX Orin 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。

04.Install Jetpack environment

Installing the Jetpack Environment

Installing the Jetpack Environment1. Hardware Connection2. Software Connection3. Using SDK Manager3.1 Motherboard Selection3.2 STEP 13.3 STEP 23.4 STEP 33.5, STEP44, Environment Verification

Some users may need to use NVIDIA's built-in system component environment. After successfully installing the system and entering the desktop, you can follow the tutorial below to install the component environment! Since the Jetpack environment is relatively large, it is recommended to install it on an NVMe SSD system environment.

Note: The SSD included with the product contains a factory image, which includes the official NVIDIA system and motherboard environment; unless a clean system is required, please do not proceed!

The entire process requires a network connection. Some components may require a VPN. If you cannot complete the component installation, use our factory image.

1. Hardware Connection

Plug the power adapter into the Jetson AGX Orin motherboard. Connect the Type-C data cable to your Ubuntu computer or virtual machine. The other end must be connected to the Type-C port next to the 40-pin header on the Jetson AGX Orin motherboard.

Note: Installing the Jetpack component environment does not require entering flashing mode; the motherboard only needs to be powered on!

image-20260210213145962

2. Software Connection

This tutorial uses VMware Workstation 17 Pro to flash the system!

After starting the virtual machine, select in the menu bar: Virtual Machine → NVIDIA Linux for Tegra → Confirm the connection status with the virtual machine.

image-20250123100406992

3. Using SDK Manager

With the Jetson AGX Orin motherboard in normal system startup mode, connect the Ubuntu computer or virtual machine using a Type-C data cable.

3.1 Motherboard Selection

After opening SDK Manager, select according to your motherboard model: For official packages, select Jetson AGX Orin [64GB developer kit version]

image-20260211111106169

3.2 STEP 1

Check the options below, and after confirming that all selections are correct, click CONTINUE:

image-20260211111137499

3.3 STEP 2

Note: The system has already been successfully installed; do not select the Jetson Linux option.

We only need to select the required component environments: SDK Manager will automatically download all components. Once the download is complete, we can proceed to the next step.

image-20250116194450017

Enter the virtual machine password: yahboom

image-20250116194516622

3.4 STEP 3

Here, enter the username and password you set during system startup. This process takes a long time, please be patient.

image-20250116194558310

Wait for the system to download and install: A network failure occurred in the virtual machine during this process, which can be ignored. Testing showed it did not affect the flashing of component environments.

image-20250116194622869

The entire installation process takes a long time, please be patient. If the installation fails, you can restart the motherboard system and restart the SDK. Manager Installation:

image-20250116194818632

image-20250116200418604

3.5, STEP4

image-20250116203345930

4, Environment Verification

Jtop Tool

Install Jtop using the following commands:

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sudo apt update && sudo apt upgrade
sudo apt install python3-pip -y
sudo pip3 install -U jetson-stats

Note: A system restart is required after installation!

Optimal Performance Mode

Enable MAX Power Mode

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sudo nvpmodel -m 0

Alternatively, find the NVIDIA icon in the upper right corner of your desktop and change the power mode to MAXN.

image-20260211113612180

Enable Jetson clocks: CPU and GPU cores run at maximum frequency

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sudo jetson_clocks

Use the Jtop tool to view system information:

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jtop

image-20260211112540686

image-20260211112601821

Flash new system to an NVMe SSD
Backup SSD system

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