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ROSMASTER M3📖
00.Configuration and Operation Guide
  • 1.Quick start handle to control the car
  • 2.Log in to the car and view the code
  • 3.Enter the Docker (For RPI5)
  • 4.Camera and Radar Configuration (Must Read)
  • 5.Assembly video
  • 6.Modify Control Board Firmware Parameters
01.Chassis Control Course
  • 01.ROS control
  • 02.Handle control
  • 03.Keyboard control
  • 04.Robot state estimation
  • 05.Data remote visualization
  • 06.Line velocity calibration
  • 07.Angular velocity calibration
  • 08.Robot URDF model
  • 09.Line patrol automatic driving
  • 10.Patrol
02.Lidar Course
  • 01.Lidar introduction and use
  • 02.Lidar point cloud fusion and filtering
  • 03.Lidar obstacle avoidance
  • 04.Lidar tracking
  • 05.Lidar guard
  • 06.Gmapping-SLAM mapping
  • 07.Cartographer-SLAM mapping
  • 08.slam_toolbox mapping
  • 09.Lifelong mapping
  • 10.Navigation2 single-point navigation avoid
  • 11.Navigation2 multi-point navigation avoid
  • 12.Cartographer relocalization navigation
  • 13.slam_toolbox localization and navigation
  • 14.Synchronous mapping and navigation
  • 15.RTAB-Map mapping
  • 16.RTAB-Map navigation
  • 17.APP mapping and navigation
03.AI Model Basics
  • 1.AI large model types and principles
  • 2.RAG retrieval enhancement and model training samples
  • 3.Embodied intelligent robot system architecture
  • 4.Embodied intelligent functions core source code
04.AI Model Development
  • 01.Register a model service provider account
  • 02.Configuring API-KEY
  • 03.Introduction to Dify
  • 04.Basic Dify Features
  • 05.AI Large Model Development - chatbot
  • 06.Deploy the RAG knowledge base
  • 07.RAG knowledge base + chatbot
  • 08.AI agent workflow
  • 09.Custom wake-up response
  • 10.Core module testing tools
05.AI Model - Voice Version
  • 1.Semantic understand and command follow
  • 2.Multimodal visual understanding
  • 3.Multimodal visual understanding+SLAM navigation
  • 4.Intention estimation
06.AI Model - Text Version
  • 1.Semantic understand and command follow
  • 2.Multimodal visual understanding
  • 3.Multimodal visual understanding+SLAM navigation
  • 4.Intention estimation
07.Road Network Planning and Navigation
  • 1.Introduction and Quick Start
  • 2.Constructing a Pose Map
  • 3.Road Network Labelling
  • 4.Inter-Road Network Planning and Navigation
  • 5.Free-Pose Road Network Navigation
  • 6.Path Replanning
08.Autonomous Driving expand(Need purchase track map)
  • 01.Environment Setup & Precautions
  • 02.YOLO Environment Configuration
  • 03.Data Collection
  • 04.Data Annotation
  • 05.YOLOv11 Model Training
  • 06.Model Format Conversion
  • 07.Vehicle Centerline Calibration
  • 08.Lane Detection
  • 09.Lane-Keeping Autonomous Driving
  • 10.Traffic Sign Recognition
  • 11.Comprehensive Autonomous Driving Applications
  • 12.Autonomous Driving Debugging Module
  • 13.Road Network Planning with Track Map
  • 14.Road Network Planning with Traffic Sign Recognition
  • 15.AI Model with Road Network Planning
  • 16.AI Model with Track Map and SLAM Navigation
  • 17.AI Model with Road Network Planning and Autonomous Driving
09.Depth Camera Course
  • 01.Dabai_DCW2 Camera Introduction
  • 02.Nuwa-HP60C Camera Introduction
  • 03.Depth Pseudo-Color Image
  • 04.Depth Camera Distance Measurement
  • 05.Wood Block Volume Measurement
  • 06.Edge Detection
  • 07.YOLOv11 Object Detection
  • 08.YOLOv11 Object Tracking
  • 09.Color Following
  • 10.Face Following
  • 11.QR Code Following
  • 12.Machine Code Following
  • 13.KCF Object Tracking
  • 14.QR Code Motion Control
  • 15.AR Vision
10.Mediapipe Visual Course
  • 01.Hand Detection
  • 02.Posture Detection
  • 03.Overall Detection
  • 04.Facial Landmark Detection
  • 05.3D Object Recognition
  • 06.Face Detection
  • 07.Gesture Recognition
  • 08.Face Special Effects
  • 09.Brush
  • 10.Finger Control
  • 11.Palm Target Positioning
  • 12.Fingertip Trajectory Recognition
  • 13.Gesture Following
  • 14.Posture Following
  • 15.Gesture Motion Control
11.Multi-vehicle Course
  • 1.Multi-vehicle Control
  • 2.Multi-vehicle Navigation
  • 3.Multi-vehicle Platoon
12.AI Large Model Basic Course
Offline large model (Text Interaction)
  • 0. AI Large Model Mirroring Explanation
  • 1. Deployment of large-scale AI models
  • 2. Installation of the large model dialogue platform
  • 3. Meta AI Llama 3.2 model
  • 4. Alibaba Cloud Qwen3 Model
  • 5. DeepSeek DeepSeek-R1 model
  • 6. Microsoft Phi-4 mini model
  • 7. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 8. Google Gemma3 Visual Multimodal Large Model
  • 9. Llava Visual Multimodal Large Model
  • 10. Multimodal Visual Understanding Applications
  • 11.MiniCPM-V Visual Multimodal Large Model
  • 12. Multimodal Text-Based Image Application
  • 13. Multimodal Video Analysis Application
  • 14. Multimodal table scanning application
  • 15. Multimodal visual positioning applications
  • 16. Multimodal Autonomous Agent Application
Offline large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Offline speech-to-text (ASR)
  • 2. Offline Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual understanding and voice interaction
  • 5. Multimodal Text-Based Image Application
  • 6. Multimodal Video Analysis Application
  • 7. Multimodal visual positioning applications
  • 8. Multimodal table scanning application
  • 9. Multimodal Autonomous Agent Applications
  • 10. AI large model offline voice assistant
Online large model (Text Interaction)
  • 1. OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal visual understanding applications
  • 3. Multimodal visual positioning applications
  • 4. Multimodal table scanning application
  • 5. Multimodal Autonomous Agent Applications
Online large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Online speech-to-text (ASR)
  • 2. Online Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual and voice interaction
  • 5. Multimodal visual positioning applications
  • 6. Multimodal table scanning application
  • 7. Multimodal Autonomous Agent Applications
  • 8. AI large model online voice assistant
13.Control Board Course
1.Development environment setup
  • 1.Introduction to the Control Board
  • 2.Set up the STM32CUBEIDE development environment
  • 3.Burning STM32 firmware using SWD
  • 4.Burning STM32 firmware using serial port
  • 5.Compile the microros driver library
  • 6.Install and start the microros agent
  • 7.Import Project
2.Control board STM32 basic routine
  • 1.Turn on the LED light
  • 2.Button functions
  • 3.Drive the buzzer
  • 4.Serial communication
  • 5.Battery voltage detection
  • 6.Driving PWM Servo
  • 7.Drive motor
  • 8.Read motor encoder data
  • 9.PID control of motor speed
  • 10.Robot kinematics analysis theory
  • 11.Read IMU data
  • 12.Read Lidar data
  • 13.Flash access data
  • 14.Driving OLED Displays
  • 15.Driving RGB light strip
  • 16.SBUS model aircraft remote control
  • 17.USB controller remote control
  • 18.CAN bus communication
3.Control board micro_ros basic routine
  • 1.Post a topic
  • 2.Subscribe to a topic
  • 3.Multi-topic subscription and publishing
  • 4.Subscribe to the buzzer topic
  • 5.Subscribe to the bus servo topic
  • 6.Subscribe to the rate control topic
  • 7.Release Speed Topic
  • 8.Publish IMU data topic
  • 9.Publish radar data topic
14.Main Control Course
Jetson Orin Nano_NX
  • 1.Jetson Orin board introduction
  • 2.Restore the factory image system
  • 3.Backup SSD system
  • 4.SSD expansion
  • 5.Network configuration
  • 6.SSH remote login
  • 7.VNC remote control
  • 8.Remote file transfer
  • 9.Jtop tool
  • 10.Exchange space expansion
Raspberry Pi
  • 1. Introduction to Raspberry PI 5
  • 2. Raspberry PI system installation and backup
  • 3. Powering the Raspberry PI 5
  • 4. Startup of Raspberry PI 5
  • 5. Update and upgrade operating system
  • 6. Introduction to raspi-config tool
  • 7. config.txt file description
  • 8. Network Configuration
  • 9. remote access
  • 10. Transfer files remotely
  • 11. Set display resolution and rotation
  • 12. Set screen to sleep
  • 13. Play audio and video
  • 14. Using USB camera
  • 15. Using MIPI camera
  • 16. Get real-time temperature of Raspberry Pi
RDKX5
  • 1.Introduction to RDK X5 board
  • 2.Write system file
  • 3.Hardware interface description
  • 4.Install case and other accessories
  • 5.Network configuration
  • 6.Remote login
  • 7.Update system
  • 8.srpi-config user guide
  • 9.config. txt configuration file
  • 10.Self-startup setting
  • 11.RDK exclusive command usage
  • 12.Linux command usage
  • 13.GPIO readwrite operation
  • 14.Image classification algorithm
  • 15.Use USB camera
  • 16.Use MIPI camera
  • 17.Binocular camera depth algorithm
15.YOLOv11 Development (ORIN)
  • 1.YOLO environment construction
  • 2.CLI use
  • 3.Object detection
  • 4.Instance segmentation
  • 5.Pose estimation
  • 6.Image classification
  • 7.Oriented object detection
  • 8.Model conversion
  • 9.Dataset annotation
  • 10.Model Training_Conversion
  • 11.Model prediction
16.YOLOv11 Development(RDKX5)
  • 1.YOLO environment construction
  • 2.CLI use
  • 3.Object detection
  • 4.Instance segmentation
  • 5.Pose estimation
  • 6.Image classification
  • 7.Oriented object detection
  • 8.Model prediction
  • 9.Model Quantization
17.YOLOv11 Development (RPI)
  • 1.YOLO environment construction
  • 2.CLI use
  • 3.Object detection
  • 4.Instance segmentation
  • 5.Pose estimation
  • 6.Image classification
  • 7.Oriented object detection
  • 8.Model conversion
  • 9.Model prediction
18.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
19.ROS2 Basic Course
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 3.ROS2 development environment
  • 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
20.Docker Course
  • 1、Docker overview and docker installation
  • 2、Common commands for docker image containers
  • 3、Docker images deeply understand and publish images
  • 4、Docker hardware interaction and data processing
  • 5、Enter the bot's docker container
  • 6、Robot development environment construction in Docker
21.Image Processing Basics 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. Image cutting
  • 8. Image translation
  • 9. Image Mirroring
  • 10. Affine Transformation
  • 11. Image Rotation
  • 12. Perspective Transformation
  • 13. Grayscale processing
  • 14. Image Binarization
  • 15. Edge Detection
  • 16. Line drawing
  • 17. Rectangle and circle drawing
  • 18. Drawing text and pictures
Download
  • Mapping_APP(iOS_Android)
  • MainBoard_AI_Pure_System
  • Robot_Image_System_File
  • Code-Firmware
  • Instruction_Manual
  • VM_File
  • Software_Tools
  • Firmware_DriverFile
  • 3D_Model_File
  • ROS2_Basic_VM
  • Other_Annex
Download ZIP

Welcome to ROSMASTER M3 repository

08.Robot URDF model

Robot URDF Model

Robot URDF Model1. Course Content2. Preparations2.1 Content Description3. Start the Program4. Source Code Analysis4.1 Components4.2 Joints

1. Course Content

Basic: Learn how to view the robot's model file and use the GUI debugging tool window to check the movement of the model's joints by sliding the progress bar.

Advanced: Understand the composition of a URDF description file.

 

2. Preparations

2.1 Content Description

For Raspberry Pi boards, you need to open a terminal on the host machine, enter the command to get into the Docker container, and then input the commands mentioned in this lesson in the terminal within the Docker container. A tutorial on how to enter the Docker container from the host can be found in this product's guide [00.Configuration and Operation Guide]-[3.Enter the Docker (For RPI5)]. For ORIN and RDK boards, you can directly open a terminal and enter the commands mentioned in this lesson.

3. Start the Program

  • Enter the command in the terminal:

For Raspberry Pi 5 users, if the ROS container is not started, you need to start it first,

bringup_m3

Open a terminal inside the container,

xxxxxxxxxx
exec_m3

Enter the command,

xxxxxxxxxx
ros2 launch m3_description display.launch.py gui:=true

The startup interface is as follows:

image-20251205154706378

 

  • Visualize the TF coordinate tree

Click on the left menu bar, then check the box for TF to visualize the TF coordinate tree.

image-20251205154847383

 

  • Test rotating joints

Click and drag the slider in the joint_state_publisher panel to adjust the rotation of the corresponding joint. For the ROSMASTER-M3 robot, the only movable joints are the four drive wheels.

image-20251205155342736

 

4. Source Code Analysis

Robot model description file path:

xxxxxxxxxx
~/yahboomM3_ws/code_ws/src/m3_description/urdf/ROSMASTER-M3.xacro

Robot model launch file path:

xxxxxxxxxx
~/yahboomM3_ws/code_ws/src/m3_description/launch/display.launch.py

 

  • URDF, which stands for Unified Robot Description Format, is a robot model file described in XML format.
​x
<?xml version="1.0" encoding="utf-8"?>
​
<robot name="ROSMASTER-M3" xmlns:xacro="http://ros.org/wiki/xacro">
​
  <xacro:arg name="prefix" default="" />                                      <!-- namespace -->
  <xacro:arg name="laser_type" default="dual" />                              <!-- Laser sensor type (single/dual) -->    
  <xacro:arg name="camera_type" default="as_hp60c" />                         <!-- Depth camera type -->
​
  <xacro:include filename="$(find m3_description)/urdf/materials.xacro"/>     <!-- Model color properties -->
  <xacro:include filename="$(find m3_description)/urdf/common_base.xacro" />  <!-- Robot chassis template -->
  <xacro:include filename="$(find m3_description)/urdf/laser.xacro" />        <!-- Lidar template -->
​
  <xacro:common_base prefix="$(arg prefix)"  camera_type="$(arg camera_type)" /><!-- Instantiating the robot chassis -->
  <xacro:laser laser_type="$(arg laser_type)" prefix="$(arg prefix)" />         <!-- Instantiate lidar -->
​
</robot>

The first line is a required XML item, describing the XML version information.

The second line describes the current robot's name; all information about the current robot is contained within the <robot> tag.

xxxxxxxxxx
  <!-- base_footprint projection point -->
  <link
    name="${prefix}base_footprint">
  </link>
  <joint
    name="${prefix}base-Joint"
    type="fixed">
    <origin
      xyz="0 0 0.03"
      rpy="0 0 0" />
    <parent
      link="${prefix}base_footprint" />
    <child
      link="${prefix}base_link" />
  </joint>
​
​
  <!-- base_link chassis -->
  <link
    name="${prefix}base_link">
    <inertial>
      <origin
        xyz="-0.02984496350171 -0.000481153572635691 0.0765287728161752"
        rpy="0 0 0" />
      <mass
        value="0.99934444005899" />
      <inertia
        ixx="0.00160080186836152"
        ixy="3.98571758764143E-06"
        ixz="-0.000131328647411587"
        iyy="0.00221164246632588"
        iyz="5.5986256573897E-07"
        izz="0.00344837201415694" />
    </inertial>
    <visual>
      <origin
        xyz="0 0 0"
        rpy="0 0 0" />
      <geometry>
        <mesh
          filename="package://m3_description//meshes/base_link.STL" />
      </geometry>
      <material
        name="">
        <color
          rgba="0.776470588235294 0.756862745098039 0.737254901960784 1" />
      </material>
    </visual>
    <collision>
      <origin
        xyz="0 0 0"
        rpy="0 0 0" />
      <geometry>
        <mesh
          filename="package://m3_description//meshes/base_link.STL" />
      </geometry>
    </collision>
  </link>
​

 

4.1 Components

  • link: Can be thought of as a person's arm.
  • joint: Can be thought of as a person's elbow joint.
  • Relationship between link and joint: Two links are connected by a joint. Imagine an arm with a forearm (link) and an upper arm (link) connected by an elbow joint (joint).
  • In the URDF descriptive language, link is used to describe physical properties:
  • Visual display is described by the <visual> tag.
  • Collision properties are described by the <collision> tag.
  • Physical inertia is described by the <inertial> tag (less commonly used).

Tag Descriptions:

  • origin: Describes pose information; the xyz attribute describes the coordinate position in the larger environment, and the rpy attribute describes its own orientation.
  • mass: Describes the mass of the link.
  • inertia: The inertial reference frame. Due to the symmetry of the rotational inertia matrix, only the 6 upper triangular elements ixx, ixy, ixz, iyy, iyz, izz are needed as attributes.
  • geometry: Describes the shape; the mesh attribute's main function is to load texture files, and the filename attribute specifies the path to the texture file.
  • material: Describes the material; the name attribute is required, can be empty, and can be repeated. The rgba attribute within the <color> tag describes red, green, blue, and alpha (transparency), separated by spaces. The color range is [0-1].

4.2 Joints

Introduction

Describes the relationship between two joints, motion position and velocity limits, and kinematic and dynamic properties.

Joint Types:

  • fixed: A fixed joint. Does not allow movement and serves as a connection.
  • continuous: A rotational joint. Can rotate continuously with no angle limits.
  • revolute: A rotational joint. Similar to continuous, but with angle limits.
  • prismatic: A sliding joint. Moves along an axis, with position limits.
  • floating: A floating joint. Has six degrees of freedom (3T3R).
  • planar: A planar joint. Allows for translation or rotation on a plane.
  • In the <joint> tag, the name attribute is required, describes the joint's name, and must be unique.
  • In the <joint> tag, the type attribute corresponds to one of the six joint types.

Tag Descriptions

  • origin: A sub-tag that refers to the relative position of the rotating joint in the parent's coordinate system.

  • parent, child: Sub-tags that represent the two links to be connected; parent is the reference, and child rotates around the parent.

  • axis: A sub-tag that indicates which axis (xyz) the child link rotates around and the amount of rotation around that fixed axis.

  • limit: A sub-tag that primarily restricts the child. The lower and upper attributes limit the range of rotation in radians, the effort attribute limits the force range during rotation (positive/negative values, in Newtons or N), and the velocity attribute limits the speed of rotation (in meters/second or m/s).

     

 

 

 

 

 

 

 

Angular velocity calibration
Line patrol automatic driving

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