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JetCobot📖
1.Introduction to the Jetcobot
  • 0.Unboxing
  • 1 Version Configuration Instructions
  • 2. Power adapter usage specifications
  • 3. Common Problems and Solutions
  • 4. First-time use instructions
  • 5. Get started
  • 6. Open and close the virtual desktop
2.Assembly and assembly tutorial
  • Installation Video
3.Linux operating system
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Static IP and hotspot mode
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
4.Jupyter Lab Basic Course
  • 1. Read the document before operation
  • 2. JupyterLab environment construction tutorial
  • 3. JupyterLab Basic Usage Tutorial
  • 4. JupyterWidgets Configuration Tutorial
  • 5. Getting Started Tutorial for JupyterWidgets Controls
5.Basic courses of main control board
  • 1. Introduction to the main control board
  • 2. Burn the system image
  • 3. Re-read the burned image
  • 4. System startup
  • 5. System and desktop introduction
  • 6. System expansion
  • 7. Network Configuration
  • 8. SSH remote login and file transfer
  • 9. VNC Remote Login
  • 10. System backup
  • 11. Increased swap space
  • 12. Use of Jtop
6.GPIO hardware control course
  • 1.GPIO library API usage
  • 2. Hardware library configuration
  • 3. Pin reading function
  • 4. Pin level output control
  • 5. Control LED
  • 6. External device serial communication
  • 7.I2C communication
7.Jetson-inference vision course
  • 1. Install Jetcam (optional)
  • 2. Install TensorFlow (optional)
  • 3. Jetson-inference environment construction (optional)
  • 4. Hello AI World
  • 5. Image Classification Reasoning
  • 6. Object Detection Reasoning
  • 7. Semantic Segmentation
8.Opencv basic course
  • 1. Introduction to Open Source CV
  • 2. Image reading and display
  • 3. Image writing
  • 4. Image quality
  • 5. Pixel Operation
  • 6. Image zoom
  • 7. Picture cut
  • 8. Picture pan
  • 9. Picture mirroring
  • 10. Affine transformation
  • 11. Picture rotation
  • 12. Perspective transformation
  • 13. Grayscale processing
  • 14. Binary image
  • 15. Edge green detection
  • 16. Line segment drawing
  • 17. Rectangular circle drawing
  • 18. Text and picture drawing
9.ROS 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
10.ROS+OpenCV course
  • 1.QR code
  • 2.Human pose estimation
  • 3.Target Detection
  • 4.AR vision
  • 5.AR QR code
  • 6.ROS+Opencv basics
  • 7.Face recognition
  • 8.harris corner detection
  • 9.Target tracking algorithm
  • 10.Contour moment
  • 11.Polygon outline
  • 12.Discrete fourier transform algorithm
  • 13.Edge detection algorithm
  • 14.Face detection algorithm
  • 15.Optical flow detection algorithm
  • 16.Contour detection
  • 17.General contour detection
  • 18.Feature point tracking
  • 19.HLS color filtering
  • 20.Hough circle detection
  • 21.Hough linear detection
  • 22.HSV color filtering
  • 23.LK optical flow algorithm
  • 24.Detection algorithm
  • 25.Phase dependent displacement detection
  • 26.Image pyramid sampling algorithm
  • 27.RGB color filtering
  • 28.Clear background detection algorithm
  • 29.Simplified optical flow algorithm
  • 30.Simple filter
  • 31.Threshold image processing
  • 32.Watershed segmentation algorithm
11.Robotic arm control course
  • 1.Send data
  • 2.Read data
  • 3.Control robotic arm joint angle
  • 4.Control coordinates of robotic arm end
  • 5.Control robotic arm posture
  • 6.Handle control robotic arm
  • 7.Calibrate robotic arm joint
  • 8.Calibrate robotic arm gripper
12.AI visual basic ourse
  • 1.Camera driver
  • 2.Block color calibration
  • 3.Color recognition
  • 4.Face detection
  • 5.Gesture recognition
  • 6.Model training
  • 7.Garbage recognition
13.Mediapipe course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall detection
  • 4.Face detection
  • 5.Face recognition
  • 6.Face effects
  • 7.3D object recognition
  • 8.Brush
  • 9.Finger control
  • 10.Gesture recognition
14.AI visual tracking course
  • 1.PID algorithm basics
  • 2.Color block positioning
  • 3.Color block tracking
  • 4.Face positioning
  • 5.Face tracking
  • 6.Fingertip trajectory recognition
  • 7.Mediapipe gesture control robotic arm action group
  • 8.Mediapipe arm posture control robotic arm
  • 9.Mediapipe palm arm target positioning
  • 10.Mediapipe palm recognition and tracking control robotic arm
  • 11.Apriltag tag code recognition
  • 12.Apriltag tag code tracking
  • 13.KCF object tracking
15.AI visual grabbing course
  • 1.Gesture recognition stacking blocks
  • 2.Color recognition grab blocks
  • 3.Apriltag recognition grabbing blocks
  • 4.Catch game
  • 5.Color sorting
  • 6.Color stacking
  • 7.apriltag sorting
  • 8.apriltag stacking
  • 9.Garbage sorting
  • 10.Garbage stacking
  • 11.Color interaction
16.URDF Model course
  • 1.URDF model of the robotic arm
  • 2.URDF model controls the real robotic arm
17.Kinesiology advanced course
  • 1.Movelt configuration
  • 2.MoveIt control the real machine
  • 3.Moves randomly
  • 4.Movelt kinematic design
  • 5.Movelt cartesian path
  • 6.Movelt collision detection
  • 7.Movelt scene design
18.Jetson Orin SUPER -Introduction to the Jetcobotnew
  • 1. Version Configuration Instructionsnew
  • 2. Power adapter usage specificationsnew
  • 3. Common Problems and Solutionsnew
  • 4. First-time use instructionsnew
  • 5. Get startednew
  • 6. Open and close the virtual desktopnew
19.Jetson Orin SUPER -Assembly and assembly tutorial
  • Installation Videonew
20.Jetson Orin SUPER -Linux operating systemnew
  • 1.Introduction to Linux systemnew
  • 2.Ubuntu file systemnew
  • 3.Ubuntu common commandsnew
  • 4.Ubuntu common editorsnew
  • 5.Ubuntu software operation commandsnew
  • 6.Virtual machine installationnew
  • 7.SSH remote controlnew
  • 8.VNC remote controlnew
  • 9.Transfer files remotelynew
  • 10.Driver library and communicationnew
  • 11.Static IP and hotspot modenew
  • 12.Bind device IDnew
  • 13.Capacity expansion and resource allocationnew
  • 14.Update system software sourcesnew
  • 15.Set root user passwordnew
  • 16.sudo free passwordnew
  • 17.Connect to WiFi networknew
  • 18.View system versionnew
  • 19.Customized service managementnew
  • 20.Back up system imagenew
21.Jetson Orin SUPER -Jupyter Lab Basic Course
  • 1. Read the document before operationnew
  • 2. JupyterLab environment construction tutorialnew
  • 3. JupyterLab Basic Usage Tutorialnew
  • 4. JupyterWidgets Configuration Tutorialnew
  • 5. Getting Started Tutorial for JupyterWidgets Controlsnew
22.Jetson Orin SUPER -Basic motherboard usage course
  • 1. Motherboard Introductionnew
  • 2. Restore the factory image systemnew
  • 3. System startupnew
  • 4. System and desktop introductionnew
  • 5.VNC Remote Controlnew
  • 6. System expansionnew
  • 7. Network Configurationnew
  • 8.SSH remote loginnew
  • 9. Remote file transfernew
  • 10. Chinese input methodnew
  • 11. Use of Jtop toolnew
  • 12. Swap space expansionnew
  • 13.Backup SSD systemnew
  • 14.Jetpack old system upgraded to SUPER system
23.Jetson Orin SUPER -GPIO hardware control course
  • 1.GPIO library API usagenew
  • 2.Hardware library configurationnew
  • 3.Pin reading functionnew
  • 4.Pin level output controlnew
  • 5.Control LEDnew
  • 6.External device serial communicationnew
  • 7.I2C communicationnew
24.Jetson Orin SUPER -YOLO11 development
  • 01.YOLO environment constructionnew
  • 02.CLI usenew
  • 03.Object detection
  • 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
25.Jetson Orin SUPER -OpenCV course
  • 1. Introduction to Open Source CVnew
  • 2. Image reading and displaynew
  • 3. Image writingnew
  • 4. Image qualitynew
  • 5. Pixel Operationnew
  • 6. Image zoomnew
  • 7. Picture cutnew
  • 8. Picture pannew
  • 9. Picture mirroringnew
  • 10. Affine transformationnew
  • 11. Picture rotationnew
  • 12. Perspective transformationnew
  • 13. Grayscale processingnew
  • 14. Binary imagenew
  • 15. Edge green detectionnew
  • 16. Line segment drawingnew
  • 17. Rectangular circle drawingnew
  • 18. Text and picture drawingnew
26.Jetson Orin SUPER -ROS2 basic course
  • 1. Introduction to ROS2new
  • 2.ROS2 install Humblenew
  • 3.ROS2 development environmentnew
  • 4.ROS2 workspacenew
  • 5.ROS2 function packagenew
  • 6.ROS2 nodenew
  • 7.ROS2 topic communicationnew
  • 8.ROS2 service communicationnew
  • 9.ROS2 action communicationnew
  • 10.ROS2 custom interface messagenew
  • 11.ROS2 parameter service casenew
  • 12.ROS2 meta-function packagenew
  • 13.ROS2 distributed communicationnew
  • 14.ROS2 DDSnew
  • 15.ROS2 time related APInew
  • 16.ROS2 common command toolsnew
  • 17.ROS2 rviz2 usenew
  • 18.ROS2 rqt toolboxnew
  • 19.ROS2 Launch startup file configurationnew
  • 20.ROS2 recording and playback toolnew
  • 21.ROS2 URDF modelnew
  • 22.ROS2 Gazebo simulation platformnew
  • 23.ROS2 TF2 coordinate transformationnew
27.Jetson Orin SUPER -Advanced vision course
  • 1.QR codenew
  • 2.Human pose estimationnew
  • 3.Target Detectionnew
  • 4.AR visionnew
  • 5.ROS+Opencv Basicsnew
28.Jetson Orin SUPER -Robotic Arm Control Course
  • 1. Sending Datanew
  • 2. Read datanew
  • 3. Control the joint angle of the robotic armnew
  • 4. Control the coordinates of the end of the robot armnew
  • 5. Control the posture of the robotic armnew
  • 6.Handle remote control robotic armnew
  • 7. Calibrate the robot arm jointsnew
  • 8. Calibrate the robot grippernew
29.Jetson Orin SUPER -AI Vision Basic Course
  • 1. Camera drivernew
  • 2. Color threshold adjustment and color block calibrationnew
  • 3. Color recognitionnew
  • 4. Face Detectionnew
  • 5. Gesture Recognitionnew
  • 6. Garbage Identificationnew
30.Jetson Orin SUPER -Mediapipe Development Course
  • 1. Hand detectionnew
  • 2. Posture detectionnew
  • 3. Overall detectionnew
  • 4.FaceMeshnew
  • 5. Face Detectionnew
  • 6. Face effectsnew
  • 7. 3D Object Recognitionnew
  • 8. Brushnew
  • 9. Finger controlnew
  • 10. Gesture Recognitionnew
31.Jetson Orin SUPER -AI visual tracking course
  • 1.PID algorithm basicsnew
  • 2. Color block positioning experimentnew
  • 3. Color block tracking experimentnew
  • 4. Face location experimentnew
  • 5. Face tracking experimentnew
  • 6. Fingertip trajectory recognitionnew
  • 7.Mediapipe gesture control robotic arm action groupnew
  • 8.Mediapipe arm posture control robotic armnew
  • 9. Mediapipe palm arm target positioningnew
  • 10. Mediapipe identifies and tracks your palm to control the robotic armnew
  • 11. Apriltag label code recognitionnew
  • 12. Apriltag label code trackingnew
  • 13.KCF Object Trackingnew
32.Jetson Orin SUPER -AI Visual Capture Course
  • 1. Gesture recognition stacking blocksnew
  • 2. Color recognition grab blocksnew
  • 3. Apriltag recognition and grabbing building blocksnew
  • 4.Catch gamenew
  • 5. Color sortingnew
  • 6. Color stackingnew
  • 7. Apriltag sortingnew
  • 8. Apriltag stackingnew
  • 9. Garbage sortingnew
  • 10. Garbage dumpnew
  • 11.Color interactionnew
33.Jetson Orin SUPER -Robotic Arm URDF Model Course
  • 1. Robotic arm URDF modelnew
  • 2. URDF model controls the real robot armnew
34.Jetson Orin SUPER -Moveit advanced kinematics course
  • 1.Movelt Configurationnew
  • 2. Use of MoveItnew
  • 3. MoveIt drives the real machinenew
  • 4. MoveIt Random Movenew
  • 5.Movelt positive kinematics designnew
  • 6.Movelt inverse kinematics designnew
  • 7.Movelt Cartesian pathnew
  • 8.Movelt scene designnew
  • 9.Movelt Collision Detectionnew
35.FAQnew
  • 1.Using your own Jetson board, JetCobot cannot start normally
Download
  • Instruction_Manual
  • SystemFile_for_NANO4GB
  • SystemFile_For_OrinNANO
  • SystemFile_For_OrinNX
  • VM_File
  • Code
  • 3D Model File
  • Jetson_Boot_USB.tar.gz
  • ROS2_Basic_VM
Download ZIP

Welcome to JetCobot repository

21.ROS2 URDF model

21. ROS2 URDF Model

1. Introduction to URDF

The modeling method in ROS is called URDF, which stands for Unified Robot Description Format. It not only clearly describes the robot model itself, but also describes the robot's external environment. URDF model files use the XML format.

SolidWorks model to URDF plugin: sw_urdf_exporter - ROS Wiki

2. Robot Components

When modeling and describing a robot, we first need to be familiar with the robot's components and parameters. For example, a robot is generally composed of four major components: hardware structure, drive system, sensor system, and control system. Common robots on the market, whether mobile robots or robotic arms, can be broken down into these four components.

image-20220528144350325

  • The hardware structure refers to the tangible components, such as the chassis, housing, and motors.
  • The drive system is the equipment that enables these components to function properly, such as the motor driver and power management system.
  • The sensor system includes encoders on the motor, an onboard IMU, installed cameras, radar, and more, enabling the robot to sense its own state and external environment.
  • The control system is the primary vehicle for our development process, typically a computing platform like a Raspberry Pi or a computer, along with its operating system and application software.

The robot modeling process follows a similar approach, using a modeling language to clearly describe each component of the robot and then assemble them.

3. URDF Syntax

3.1. Link Description

The tag is used to describe the appearance and physical properties of a robot's rigid body. Appearance includes size, color, and shape, while physical properties include mass, inertia matrix, collision parameters, and so on.

image-20220528144534685

Taking this robotic arm link as an example, its link description is as follows:

image-20220528144549092

The name in the link tag represents the name of the link. We can customize it, and this name will be used when connecting joints to links in the future.

The section of the link describes the robot's appearance. For example:

  • represents the geometric shape. is used to call a pre-designed blue appearance in 3D software. This is the STL file, which looks identical to the real robot.
  • represents the offset of the coordinate system relative to the initial position, including translation in the x, y, and z directions, and roll, pitch, and raw rotations. If no offset is required, all values are 0.

The second section, , describes the collision parameters. While the content appears to be the same as , including and , there are actually significant differences.

  • focuses on describing the robot's appearance, that is, its visual effects.
  • describes the robot's state during motion, such as how contact with the outside world is considered a collision.

In this robot model, the blue part is described using . In actual control, such a complex appearance requires high computational power for collision detection. To simplify the calculations, we've simplified the collision detection model to a cylinder outlined in green, which is the shape described by in . The coordinate system offset is similar and can describe the offset of the rigid body's center of mass.

image-20220528144603646

For mobile robots, links can also be used to describe the body, wheels, and other components of the robot.

3.2 Joint Description

Rigid bodies in a robot model must ultimately be connected through joints to generate relative motion.

Joints in URDF have six types of motion.

image-20220528144655899

  1. Continuous: This describes rotational motion. It can rotate infinitely around a specific axis. For example, the wheels of a cart fall into this category.
  2. Revolute: This is also a revolute joint. Unlike the continuous type, it cannot rotate infinitely but has angle limits. For example, the two links in a robotic arm fall into this category.
  3. Prismatic: This is a sliding joint. It can translate along a specific axis and also has position limits. Linear motors typically use this type of motion.
  4. Fixed: This is the only type of joint that doesn't allow for movement, but it's still quite commonly used. For example, a camera link mounted on a robot doesn't change its relative position. In this case, the connection type used is Fixed.
  5. Floating: This is a floating joint. The sixth type, Planar, is a planar joint. These two are relatively less commonly used.

image-20220528144722751

In a URDF model, each link is described using an XML file, such as the name of the joint and the type of motion.

image-20220528144729633

  • parent tag: describes the parent link;
  • child tag: describes the child link, which moves relative to the parent link;
  • origin: indicates the relationship between the two link coordinate systems, represented by the red vector in the image, which can be understood as how the two links are mounted together;
  • axis: indicates the unit vector of the joint's motion axis. For example, if z is equal to 1, the rotation is about the positive z-axis;
  • limit: indicates any limitations on the motion, such as minimum position, maximum position, and maximum speed.

4. Complete Robot Model

image-20220528144900705

Finally, all the link and joint tags describe and combine each part of the robot. Placed within a single robot tag, this forms the complete robot model.

image-20220528144824234

So, when looking at a URDF model, don't rush to delve into the details of each block of code. First, look for links and joints to understand the robot's components. Once you understand the overall picture, then delve into the details.

4.1. Creating a Robot Model

Using the muto model as an example, copy the yahboomcar_description package from this tutorial's folder to the src directory of your workspace:

image-20250905184735806

  • urdf: Stores the robot model's URDF or XACR file
  • meshes: Stores the model rendering files referenced in the URDF
  • launch: Stores the relevant startup files
  • rviz: Stores the Rviz configuration file

Then compile the package.

xxxxxxxxxx
colcon build --packages-select yahboomcar_description

image-20250905184908066

4.2. Model Visualization

  • Refresh the environment variables and run the launch command.
xxxxxxxxxx
ros2 launch yahboomcar_description display.launch.py

Rviz will automatically launch and display the robot model:

image-20250905185113862

ROS2 recording and playback tool
ROS2 Gazebo simulation platform

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