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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
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  • 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。

16.ROS2 common command tools

16. ROS2 Common Command Tools

1. Package Management Tool ros2 pkg

1.1. ros2 pkg create

Function: Creates a package. When creating a package, you must specify the package name, compilation method, dependencies, etc.

Format:

xxxxxxxxxx
ros2 pkg create <package_name> --build-type <build-type> --dependencies <dependencies>

In the ros2 command:

  • pkg: Indicates the functions associated with the package;
  • create: Indicates the creation of a package;
  • package_name: Required: The name of the new package;
  • build-type: Required: Indicates whether the newly created package is C++ or Python. If using C++ or C, follow ament_cmake; if using Python, follow ament_python;
  • dependencies: Optional: Indicates the package's dependencies. C++ packages must include rclcpp; Python packages must include rclpy, as well as other required dependencies.

1.2, ros2 pkg list

Function: View the list of packages in the system

Format:

xxxxxxxxxx
ros2 pkg list

image-20230427154146879

1.3. ros2 pkg executables

Function: View all executable files in a package

Format:

xxxxxxxxxx
ros2 pkg executables pkg_name

image-20230427154419005

2. Node Run ros2 run

Function: Run the node program in the package

Format:

xxxxxxxxxx
ros2 run pkg_name node_name
  • pkg_name: Package name
  • node_name: The name of the executable program

image-20230427155359745

3. Node-Related Tools: ros2 node

3.1. ros2 node list

Function: Lists all node names in the current domain

Format:

xxxxxxxxxx
ros2 node list

image-20230427155655753

3.2. ros2 node info

Function: View detailed node information, including subscriptions, published messages, enabled services, and actions.

Format:

xxxxxxxxxx
ros2 node info node_name
  • node_name: The name of the node to be viewed.

image-20230427160001101

4. Topic-Related Tools: ros2 topic

4.1. ros2 topic list

Function: List all topics in the current domain

Format:

xxxxxxxxxx
ros2 topic list

image-20230427160351051

4.2. ros2 topic info

Function: Display topic message type and number of subscribers/publishers

Format:

xxxxxxxxxx
ros2 topic info topic_name
  • topic_name: The name of the topic to be queried.

image-20230427160625594

4.3, ros2 topic type

Function: View the message type of a topic

Format:

xxxxxxxxxx
ros2 topic type topic_name
  • topic_name: The name of the topic type to be queried.

image-20230427161056536

4.4, ros2 topic hz

Function: Display the average publishing frequency of a topic.

Format:

xxxxxxxxxx
ros2 topic hz topic_name
  • topic_name: The name of the topic whose frequency you want to query.

image-20230427161721650

4.5, ros2 topic echo

Function: Print topic messages on the terminal, similar to a subscriber.

Format: ros2 topic echo topic_name

  • topic_name: The name of the topic whose messages you want to print.

image-20230427162312888

4.5, ros2 topic pub

Function: Publish a message on a specified topic on the terminal.

Format:

xxxxxxxxxx
ros2 topic pub topic_name message_type message_content
  • topic_name: The name of the topic whose messages you want to publish.
  • message_type: The data type of the topic.
  • message_content: Message content

The default is to publish at a 1Hz frequency. The following parameters can be set:

  • Parameter -1 to publish only once, ros2 topic pub -1 topic_name message_type message_content
  • Parameter -t count to publish count times, ros2 topic pub -t count topic_name message_type message_content
  • Parameter -r count to publish at a count Hz frequency, ros2 topic pub -r count topic_name message_type message_content

Example:

  • Publish velocity commands via the command line
  • Note that there is a space after each colon; otherwise, a format error will be displayed.
xxxxxxxxxx
ros2 topic pub turtle1/cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.5, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.2}}"

image-20250905163149992

5. Interface-Related Tools: ros2 interface

5.1. ros2 interface list

Function: Lists all interfaces in the current system, including topics, services, and actions.

Format:

xxxxxxxxxx
ros2 interface list

image-20230427164755075

5.2. ros2 interface show

Function: Displays the detailed information of a specified interface

Format:

xxxxxxxxxx
ros2 interface show interface_name
  • interface_name: The name of the interface to be displayed

image-20230427165057647

6. Service-Related Tools ros2 service

6.1. ros2 service list

Function: Lists all services in the current domain

Format:

xxxxxxxxxx
ros2 interface show interface_name

image-20230427172236875

6.2, ros2 service call

Function: Call a specified service

Format:

xxxxxxxxxx
ros2 interface call service_name service_Type arguments
  • service_name: The service to be called
  • service_type: The service data type
  • arguments: The parameters required to provide the service

For example, to call the turtle spawn service

xxxxxxxxxx
ros2 service call /spawn turtlesim/srv/Spawn "{x: 2, y: 2, theta: 0.2, name: 'turtle10'}"

image-20230427173625631

ROS2 time related API
ROS2 rviz2 use

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