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ROSMASTER X3 Plus📖
1.Preparation and First Trial
  • 1.1 Wiring Introduction
  • 1.2 Precautions for battery
  • 1.3 First Trial
  • 1.4 Precautions for DIY Robotic Arm
2. Assembly steps
  • Installation Video
3.Remote control course
  • 3.1 APP remote control
  • 3.2 Model aircraft remote control
  • 3.3 Handle remote control
4.Hardware course
  • 4.1 About expansion board_V3.0
  • 4.1 About expansion board_V1.0
  • 4.2 STM32 Development
  • 4.3 Button to control the buzzer
  • 4.4 FreeRTOS application
  • 4.5 Serial communication
  • 4.6 SBUS model aircraft remote control
  • 4.7 CAN bus communication
  • 4.8 RGB colorful light bar
  • 4.9 Timer interrupt to control
  • 4.10 Control serial port servos
  • 4.11 Nine-axis attitude sensor
  • 4.12 Control motor
  • 4.13 Timer captures the encoder data
  • 4.14 Kinematic Analysis
  • 4.15 PID control robot movement
5.Basic course
  • 5.1 Update the firmware
  • 5.2 Turn off the self-starting process
  • 5.3 Install the Rosmaster driver
  • 5.4 Buzzer whistle
  • 5.5 Control PWM servo
  • 5.6 RGB colorful light bar
  • 5.7 Control motor
  • 5.8 Control robot movement
  • 5.9 Control Serial Servo
6.Linux operating system
  • 6.1 Virtual machine installation
  • 6.2 Linux basics
  • 6.3 Remote control
  • 6.4 Multi-machine communication
  • 6.5 Static IP and hotspot mode
  • 6.6 Bind the device ID
  • 6.7 Web page real-time monitor
  • 6.8 Expansion tutorial
  • 6.9.1 Jetson Nano write sytem
  • 6.9.2 Jetson Xavier NX write system
  • 6.9.3 Jetson TX2 NX write system
  • 6.9.4 Raspberry Pi write system
7.Docker-Just for pi5
  • 7.1 Docker overview and docker installation
  • 7.2 Common commands for docker image containers
  • 7.3 Docker images deeply understand and publish images
  • 7.4 Docker hardware interaction and data processing
  • 7.5 Enter the bot's docker container
  • 7.6 Robot development environment construction in Docker
  • 7.7 How customers can update docker images in the future
8.ROS basic course
  • 8.1 ROS introduction
  • 8.2 ROS installation
  • 8.3 ROS common command tools
  • 8.4 ROS workspace
  • 8.5 ROS function package
  • 8.6 ROS node
  • 8.7 ROS topic publisher
  • 8.8 ROS topic subscribers
  • 8.9 ROS service client
  • 8.10 ROS service server
  • 8.11 ROS action client
  • 8.12 ROS action server
  • 8.13 ROS custom message reception
  • 8.14 ROS-launch file
  • 8.15 ROS-TF transformation
  • 8.16 ROS parameter service
  • 8.17 ROS-rviz use
  • 8.18 ROS-rqt tool usage
  • 8.19 Topic message recording and playback
  • 8.20 urdf model introduction
  • 8.21 gazebo introduction
  • 8.22 ROS distributed communication
9.OpenCV courses
  • 9.1 Getting started with Open Source CV
  • 9.2 Geometric transformation
  • 9.3 Image processing and draw
  • 9.4 Image beautification
  • 9.5 Opencv application
  • 9.6 AR vision
  • 9.7 AR QR code
  • 9.8 ROS+Opencv foundation
  • 9.9 ROS+Opencv application
  • 9.10 Data transformation
  • 9.11 MediaPipe development
10.Robot control course
  • 10.1 PID algorithm theory
  • 10.2 Robot PID debugging
  • 10.3 Robot information release
  • 10.4 Robot keyboard control
  • 10.5 Robot handle control
  • 10.6 Robot state estimation
  • 10.7 Robot calibration
  • 10.8 Robot URDF model
11.Depth camera course
  • 11.1 How to use the Astra camera
  • 11.2 Astra camera calibration
  • 11.3 Astra Color Tracking
  • 11.4 Astra Object Tracking
  • 11.5 Visual tracking autopilot
  • 11.6 Pure visual 2D mapping
  • 11.7 RTAB-Map 3D mapping
  • 11.8 ORB_SLAM2 basics
  • 11.9 ORB_SLAM2_Octomap
12.Lidar course
  • 12.1 Lidar basic-SLAM
  • 12.1 Lidar basic-EAI
  • 12.2 Lidar avoiding
  • 12.3 Lidar guard
  • 12.4 Lidar follow
  • 12.5 Patrol game
  • 12.6 gmapping mapping algoritm
  • 12.7 hector mapping algorithm
  • 12.8 karto mapping algorithm
  • 12.9 cartographer mapping
  • 12.10 rrt_exploration mapping
  • 12.11 AMCL
  • 12.12 Navigation and avoiding
  • 12.13 APP mapping and navigation
13.Multi-robot control course
  • 13.1 Multi-machine handle control
  • 13.2 Multi-machine navigation
  • 13.3 Multi-machine formation
  • 13.4 Multi-machine surround
14.Deep learning courses
  • 14.1 KNN recognizes handwritten
  • 14.2 Basic use of TensorFlow
  • 14.3 Basic use of PyTorch(jetson)
  • 14.4 yolov5 model training(jetson)
  • 14.5 yolov5+tensorrt acceleration
  • 14.6 yolov4-tiny
15.Voice control courses
  • 0. How to use old voice module in new image
  • 15.1 Introduction of voice control-new
  • 15.2 Voice control module port-new
  • 15.3.Introduction of voice module-old
  • 15.4.Voice control module port binding-old
  • 15.5 Voice control car movement
  • 15.6 Voice control Autopilot
  • 15.7 Voice control color recogzition
  • 15.8 Voice control color tracking
  • 15.9 Voice control multi-point nagavation
16.Robotic arm control course
  • 16.1 MoveIt configuration
  • 16.2 MoveIt control the real machine
  • 16.3 MoveIt moves randomly
  • 16.4 MoveIt kinematics design
  • 16.5 MoveIt cartesian path
  • 16.6 MoveIt avoiding
  • 16.7 MoveIt scene design
  • 16.8 MoveIt trajectory planning
  • 16.9 Mediapipe palm control car
  • 16.10 Mediapipe gesture control robotic arm
  • 16.11 Mediapipe gesture control car
  • 16.12 Mediapipe arm attitude control robotic arm
  • 16.13 Mediapipe recognizes and tracks palm control robotic arm
  • 16.14 Recognizes color block and handling
  • 16.15 Autopilot to clear obstacles
17.Voice control robotic arm course
  • 17.1 Voice control robotic arm movement
  • 17.2 Voice control robotic arm learning
  • 17.3 Voice control color block transport
  • 17.4 Voice control robotic arm grip objects
  • 17.5 Voice control robotic arm garbage sorting
18.Model training Autopilot
  • 18.0 ReadMe
  • 18.1 yolov5 to train traffic signs
  • 18.2 TensorRt acceleration identification mark
  • 18.3 Road sign indication function description
  • 18.4 Collect data
  • 18.5 Training model
  • 18.6 Model transformation and application
  • 18.7 AI Autopilot
19.For Orin-Remote control course
1. APP control
  • 1. APP control
  • 2. Model aircraft control
  • 3. Handle control
2. Model aircraft control
3. Handle control
20.Orin-Hardware course
  • 1. About expansion board_V1.0
  • 1. About expansion board_V2.0
  • 2. STM32 Development environment
  • 3. Button control
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model aircraft remote control
  • 7. CAN bus communication
  • 8. RGB colorful light bar
  • 9. Timer interrupt to control PWM servo
  • 10. Control serial port servos
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor
  • 13. Timer captures the encoder data
  • 14. Robot kinematics analysis theory
  • 15. PID control robot movement
21.Orin-Basic course
  • 1. Update the firmware
  • 2. Turn off the self-starting process at startup
  • 3. Install the Rosmaster driver library
  • 4. Buzzer whistle
  • 5. Control PWM servo
  • 6. RGB colorful light bar special effects display
  • 7. Control motor
  • 8. Control robot movement
  • 9. Control Serial Servo
22.Orin-Linux operating systemnew
  • 1. Virtual machine installation and use
  • 2. Linux basics
  • 3. Remote control
  • 4. Multi-machine communication configuration
  • 5. Static IP and hotspot mode
  • 6. Bind the device ID
  • 7. Web page real-time monitoring
  • 8. Expansion tutorial
  • 9.1 Jetson Nano write sytem
  • 9.2 Jetson Xavier NX write system
  • 9.3 Jetson TX2 NX-Orin series write system
  • 9.4 Raspberry Pi write system
  • 10.Jetpack old system upgraded to SUPER system
23.Orin-Dockernew
SUPER image uses ros environment in docker
  • 1、Docker overview and docker installationnew
  • 2、Common commands for docker image containersnew
  • 3、Docker images deeply understand and publish imagesnew
  • 4、Docker hardware interaction and data processingnew
  • 5、Enter the bot's docker containernew
  • 6、Robot development environment construction in Dockernew
23.Orin-ROS basic course
  • 1.ROS introduction
  • 2.Project file structure
  • 3.Common commands and tools
  • 4.Publisher
  • 5.Subscribers
  • 6.Customize topic messages and use
  • 7.Client
  • 8.Server
  • 9.Custom service messages and usage
  • 10.TF release and monitoring
24.Orin-OpenCV courses
  • 1. Getting started with Open Source CV
  • 2. Open Source CV geometric transformation
  • 3. Open Source CV image processing and drawing text line segments
  • 4. Open Source CV image beautification
  • 5. Opencv application
  • 6. AR vision
  • 7. AR QR code
  • 8. ROS+Opencv foundation
  • 9. ROS+Opencv application
  • 10. Data transformation and point cloud
  • 11. MediaPipe development
25.Orin-Robot control course
  • 1.PID algorithm theory
  • 2.Robot PID debugging
  • 3.Robot information release
  • 4.Robot keyboard control
  • 5.Robot handle control
  • 6.Robot state estimation
  • 7.Robot calibration
  • 8.Robot URDF model
26.Orin-Depth camera course
  • 01.How to use the Astra camera
  • 02.Astra camera calibration
  • 03.Astra Color Tracking
  • 04.Astra Object Tracking
  • 05.Visual tracking autopilot
  • 06.Pure visual 2D mapping and navigation
  • 07.RTAB-Map 3D mapping navigation
  • 08.ORB_SLAM2 basics
  • 09.ORB_SLAM2_Octomap
27.Orin-Lidar course
  • 1.Lidar basic-4ROS-EAI
  • 1.Lidar basic-SLAM
  • 2.Lidar avoiding
  • 3.Lidar guard
  • 4.Lidar follow
  • 5.Patrol game
  • 6.gmapping mapping algorithm
  • 7.hector mapping algorithm
  • 8.karto mapping algorithm
  • 9.cartographer mapping algorithm
  • 10.rrt_exploration mapping algorithm
  • 11.AMCL
  • 12.Navigation and avoiding
  • 13.APP mapping and navigation
28.Orin-Multi-robot control course
  • 1.Multi-machine handle control
  • 2.Multi-machine navigation
  • 3.Multi-machine formation
  • 4.Multi-machine surround
29.Orin-Deep learning courses
  • 1.KNN recognizes handwritten digits
  • 2.Basic use of TensorFlow
  • 3.Basic use of PyTorch(jetson)
  • 4.YOLOv11Model conversion(SUPER)new
  • 5.YOLOv11Dataset annotation(SUPER)new
  • 6.YOLOv11Model conversion + tensorrt acceleration(SUPER)new
  • 7.YOLOv11Object recognition(SUPER)new
30.Orin-Voice control courses
  • 0. How to use old voice module in new image
  • 1.1 Introduction of voice module-new
  • 1.2 Introduction of voice module-old
  • 2.1 Voice control module port binding-new
  • 2.2 Voice control module port binding-old
  • 3. Voice control car movement
  • 4. Voice control Autopilot
  • 5. Voice control color recognition
  • 6. Voice control color tracking
  • 7. Voice control multi-point navigation
31.Orin-Robotic arm control course
  • 1.MoveIt configuration(VM)
  • 2.MoveIt control the real machine(VM)
  • 3.MoveIt moves randomly(VM)
  • 4.MoveIt kinematics design(VM)
  • 5.MoveIt cartesian path(VM)
  • 6.MoveIt avoiding(VM)
  • 7.MoveIt scene design(VM)
  • 8.MoveIt trajectory planning(VM)
  • 9.Mediapipe palm control car
  • 10.Mediapipe gesture control robotic arm
  • 11.Mediapipe gesture control car
  • 12.Mediapipe arm attitude control robotic arm
  • 13.Mediapipe recognizes and tracks palm control robotic arm
  • 14.Recognizes color block and handling
  • 15.Autopilot to clear obstacles
32.Orin-Voice control robotic arm course
  • 1.Voice control robotic arm movement
  • 2.Voice control robotic arm learning
  • 3.Voice control color block transport
  • 4.Voice control robotic arm grip objects
  • 5.Voice control robotic arm garbage sorting
LLM tutorial
1.Development environment
  • 0. Model usage instructions
  • 1.Environments deployment
  • 2.Dialogue platform installation
2.Jetson Nano B01
  • 1.Qwen2 model
  • 2.TinyLlama model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.Orca Mini model
  • 6.StarCoder2 model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA-Phi3
3.Jetson Orin NXNANO
  • 1.Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Codellama model
  • 7.DeepSeek-R1 model
  • 8.Orca Mini model
  • 9.StarCoder2 model
  • 10.TinyLlama model
  • 11.Expand LLaVA
  • 12.Expand LLaVA-Phi3
4.Raspberry Pi 5B
  • 1.Meta AI Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Meta AI Codellama model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA
FAQ
  • Using your own Jetson board, car cannot start normally
Download
  • RemoteCtrl_APP(iOS/Android)
  • Mapping_APP(iOS_Android)
  • SystemFile_OrinNANOSUPER
  • SystemFile_OrinNXSUPER
  • SystemFile_RPi_NANO
  • Instruction Manual
  • Code
  • Autopilot Annex
  • VM software
  • Jetson_Boot_USB.tar.gz
  • Other_Annex_File
Download ZIP
FAQ
  • 1、How to connect OLED?
  • 2、Precautions for DIY Robotic Arm

Welcome to ROSMASTER X3 Plus repository

8.20 urdf model introduction

20.urdf model introduction

URDF is the robot description format in ROS. Its full name is Unified Robot Description Format, which describes the robot's appearance, physical attributes, joint types, etc. URDF files are written in XML language. Let's first understand the commonly used XML tags in URDF files.

20.1 tag

20.1.1 Introduction

In the URDF descriptive language, links are used to describe physical properties. It can be detailed as a human arm, which represents a whole body and has the following tags:

  • tag: describes the visual display, including size\color\shape.
  • tag: describes collision properties.
  • tag: describes physical inertia.

Each link will be regarded as a coordinate system. The usage example is as follows:

<link name="link1"> 
    <visual> 
        <origin xyz="0 0 0" rpy="0 0 0" />
        <geometry> 
            <mesh filename="package://dofbot_moveit/meshes/link1.STL" /> 
        </geometry> 
        <material name=""> 
            <color rgba="0 0.627450980392157 0.235294117647059 1" /> 
        </material> 
    </visual> 
    <collision> 
        <origin xyz="0 0 0" rpy="0 0 0" /> 
        <geometry> 
            <mesh filename="package://dofbot_moveit/meshes/link1.STL" /> 
        </geometry> 
    </collision> 
</link>

The name attribute in the tag is required, describes the current link name, and is unique. In the sample code you can see the following sets of tags:

  • The tag describes the pose information; the xyz attribute describes the coordinate position in the general environment, and the rpy attribute describes its own posture.

  • The tag describes the shape; the main function of the mesh attribute is to load the texture file, and the filename attribute is the file address of the texture path. The tag also includes other tag descriptions:

    • box describes the length, width and height of the box through the size attribute.
    • cylinder is cylindrical . The length attribute describes the height of the cylinder, and the radius attribute describes the radius of the cylinder.
    • sphere spherical , describing the radius of the sphere through the radius attribute.
  • The tag describes the material; the name attribute is required, can be empty, and can be repeated. Red, green, blue, and transparency are described through the rgba attribute in the tag, separated by spaces. The color range is [0-1].

20.2 tag

20.2.1 Introduction

Describe the relationship between two joints. Movement position and speed limits. Kinematic and dynamic properties. It can be imagined as the joints of the human body, which include the following types:

  • fixed: fixed joint. No movement is allowed and it serves as a connection.
  • continuous: rotating joint. Can continue to rotate, there is no limit on the rotation angle.
  • revolute: rotate joint. Similar to continuous, there is a limit to the rotation angle.
  • prismatic: sliding joint. Move along a certain axis, with position restrictions.
  • floating: floating joint.
  • planar: plane joint.

A pair of tags also have the following sub-tags:

  • and represent two s to be connected, corresponding to the name attribute in ; use as a reference here, and rotates around .
  • refers to the relative position of the rotating joint to the coordinate system where the parent is located.
  • indicates which axis the corresponding rotates around.
  • mainly limits . The lower attribute and upper attribute limit the arc range of rotation, and the effort attribute limits the force range during rotation. (positive or negative value value, unit is Newton or N), velocity attribute limits the speed during rotation, unit is meter/second or m/s.

Sample code is as follows,

xxxxxxxxxx
<joint name="joint1" type="revolute"> 
    <origin xyz="0 0 0.06605" rpy="-0.010805 0 0" /> 
    <parent link="base_link" /> 
    <child link="link1" /> 
    <axis xyz="0 0 1" /> 
    <limit effort="30" velocity="1.0" lower="-1.5708" upper="1.5708"/> 
</joint>

20.3 tag

The tag is the top tag of the complete robot model. It is placed at the head and tail ends. It contains and . The name of the robot can be set in the tag. The usage is as follows:

xxxxxxxxxx
<robot name="robot_name">
    <link>
        ...
    </link>
    <joint>
        ...
    </joint>
    
    <link>
        ...
    </link>
    <joint>
        ...
    </joint>
<robot>

20.4 Create urdf function package

Generally, urdf files will be placed independently in a function package. Create the learn_urdf function package under src of the original workspace and enter it in the terminal.

xxxxxxxxxx
cd ~/ros_ws/src
catkin_create_pkg learn_urdf urdf xacro

Then return to the workspace, compile,

xxxxxxxxxx
cd ~/ros_ws
catkin_make

After compilation is completed, four new folders need to be created in the directory of the function package, namely:

  • urdf: used to store written urdf model files
  • meshes: used to store rendering files for links in URDF
  • launch: used to store the launch file that starts the display urdf
  • config: rviz file used to store the urdf model

20.5 Write launch to start urdf

In the launch folder under the learn_urdf function package, create a new file named display.launch and copy the following content into it,

​x
<launch>

    <param name="robot_description" command="$(find xacro)/xacro --inorder $(find learn_urdf)/urdf/dofbot.urdf" />

    <node name="joint_state_publisher_gui" pkg="joint_state_publisher_gui" type="joint_state_publisher_gui"/>
    
    <node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" />
    
</launch>

Exit after saving and reopen the terminal for input.

xxxxxxxxxx
roslaunch learn_urdf display.launch

image-20231027104402651

The GUI interface on the right can control the movement of the robotic arm through the slider. Now open rviz to display the robot arm, terminal input,

xxxxxxxxxx
rviz

image-20231027104631306

As shown in the picture above, set [Fixed Frame] to base_link, then click [Add], select [By display type], select [RobotModel], and finally click [OK].

image-20231027104857854

Parse launch files,

xxxxxxxxxx
<param name="robot_description" command="$(find xacro)/xacro --inorder $(find learn_urdf)/urdf/dofbot.urdf" />

Set the urdf model to be loaded.

xxxxxxxxxx
<node name="joint_state_publisher_gui" pkg="joint_state_publisher_gui" type="joint_state_publisher_gui"/>

Run the joint_state_publisher node to publish the joint status of the robot, and the joint can be controlled through the UI interface.

xxxxxxxxxx
<node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" />

Run the robot_state_publisher node, publish tf, and organize it into three-dimensional attitude information for publication.

Topic message recording and playback
gazebo introduction

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