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ROSMASTER M3 PRO📖
0.Configuration and Operation Guide
  • 1. Quick start handle to control the car
  • 2. Log in to the car and view the code
  • 3. Robotic Arm Calibration
  • 4. Enter the Docker (Jetson-Nano and Raspberry Pi 5 users, see here)
  • 5. Assembly video
  • 6. Modify the firmware parameters of the car control board
  • 7. Frequently Asked Questions and Precautions
  • 8. Precautions for DIY Robotic Arm
1.Chassis Control Course
  • 1.ROS control
  • 2.Handle control
  • 3.Keyboard control
  • 4.Angular velocity calibration
  • 5.Line velocity calibration
  • 6.Line patrol automatic driving
  • 7.Patrol
2.Lidar Course
  • 1.Lidar introduction and use
  • 2.Dual Lidar fusion
  • 3.Lidar obstacle avoidance
  • 4.Lidar tracking
  • 5.Lidar guard
  • 6.Gmapping-SLAM mapping
  • 7.Cartographer-SLAM mapping
  • 8.slam_toolbox mapping
  • 9.Navigation2 single-point navigation avoid
  • 10.Navigation2 multi-point navigation avoid
  • 11.Repositioning navigation
  • 12.RTAB-Map mapping
  • 13.RTAB-Map navigation
  • 14.APP mapping navigation
  • 15.Machine code handling
  • 16.Color block transport
  • 17.Navigation via Pose-Constrained Visual Relocalizationnew
3.Depth Camera Course
  • 1.Dabai_DCW2 camera introduction
  • 2.Depth pseudo-color image
  • 3.Depth camera distance measurement
  • 4.Wood block volume measurement
  • 5.Mediapipe gesture recognition
  • 6.Edge detection
  • 7.YOLOv8 object detection
  • 8.Deep learning object tracking
  • 9. Transformer Model Tracking Algorithmnew
4.Robotic Arm and 3D Space Gripping Course
  • 1.Robotic arm solution
  • 2.Robotic arm chassis linkage control
  • 3.Machine code ID sorting
  • 4.Sorting height abnormality machine code
  • 5.Tracking and gripping machine code
  • 6.Color block color sorting
  • 7.Sorting height abnormality color block
  • 8.Tracking and gripping color block
  • 9.Wood block shape sorting
  • 10.KCF tracking and gripping objects
  • 11.Medipipe gesture ID sorting machine code
  • 12.Mediapipe gesture height sorting machine code
  • 13.Desktop tracking and gripping machine code
  • 14.3D tracking machine code
  • 15.Line patrol and obstacle removal
5.Road network planning and navigationnew
  • 1. Introduction To Road Network Planning
  • 2. Build A Pose Map
  • 3. Road Network Annotation
  • 4. Planning And Navigation Between Waypoints
  • 5. Road Network Navigation In Any Pose
  • 6. Path Re-planning
6.OpenClaw Basic Coursenew
  • 1. Introduction to OpenClaw
  • 2. OpenClaw Core Concepts
  • 3. OpenClaw API-KEY Configuration
  • 4. OpenClaw Switch Models
  • 5. OpenClaw System Prompt Words
  • 6. OpenClaw Common CLI Commands
7.OpenClaw Interaction Methodnew
  • 1. OpenClaw Webchat Interaction
  • 2. OpenClaw Tui Interaction
  • 3. OpenClaw Voice Dialogue Interaction
  • 4. OpenClaw WhatsApp Interaction
8.OpenClaw Developmentnew
  • 1. OpenClaw connects to the MCP interface of the robot
  • 2. Robot CLI Command Tool
  • 3. Robot control plugin tool
  • 4. Reply bridge plugin tool
  • 5. OpenClaw multimodal vision
  • 6. OpenClaw chassis control
  • 7. OpenClaw robotic arm control
  • 8. OpenClaw skills development
  • 9. OpenClaw timed tasks
  • 10. OpenClaw multi-agent intelligent agent
  • 11. OpenClaw active interaction
  • 12. OpenClaw vector memory
9.OpenClaw Embodied intelligent applicationnew
  • 1. OpenClaw target tracking
  • 2. OpenClaw robotic arm tracking and grasping
  • 3. OpenClaw robotic arm fixed-point placement
  • 4. OpenClaw garbage sorting
  • 5. OpenClaw slam mapping and navigation
  • 6. OpenClaw navigation transfer
  • 7. OpenClaw machine code clip
  • 8. OpenClaw color line patrol
  • 9. OpenClaw visual distance measurement
10.OpenClaw scenario sandboxnew
  • 1. Map description and prop placement
  • 2. Build sand table map
  • 3. Visual relocation markers
  • 4. Map mapping markers
  • 5. OpenClaw scenario sandbox comprehensive case
11.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
12.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
13.AI Large Model (Text Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
14.AI Large Model(Voice Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
15.Mediapipe Visual Course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall detection
  • 4.Facial Landmark Detection
  • 5.Face detection
  • 6.Face special effects
  • 7.3D object recognition
  • 8.Brush
  • 9.Finger control
  • 10.Palm target positioning
  • 11.Fingertip trajectory recognition
  • 12.Fingertip gesture control robotic arm
  • 13.Gesture grabbing and releasing objects
  • 14.Finger control robotic arm
  • 15.Medipipe gesture control robotic arm action group
16.MoveIt2 Simulation Course
  • 1.MovelT2 configuration
  • 2.MovelT2 simulation-reality linkage
  • 3.Random movement
  • 4.Forward kinematics design
  • 5.Inverse kinematics design
  • 6.Cartesian path
  • 7.Trajectory planning
  • 8.Collision detection
  • 9.Scene design
17.Multi-vehicle Course
  • 1.Multi-vehicle chassis control
  • 2.Multi-vehicle robotic arm control
  • 3.Multi-vehicle navigation
  • 4.Multi-vehicle formation
18.Control Board Course
  • 1.Development environment setup
  • 2.Control board STM32 basic routine
  • 3.Control board micro_ros basic routine
19.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
20.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
21.Main Control Course
Jetson Nano B01
  • 1. Introduction to the Jetson Nano B01 SUB Board
  • 2. Burn the system image
  • 3. Re-read the memory card or USB drive that has been burned
  • 4. Startup system
  • 5. Jetson Nano B01 System and Desktop Introduction
  • 6. Memory card or USB flash drive expansion
  • 7. Network Configuration
  • 8. SSH remote login & file transfer
  • 9. VNC Remote Login
  • 10. Jetson Nano B01 system backup
  • 11. Jetson Nano Swap space increased
  • 12. Installation and use of Jtop
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
22.Linux System Course
  • 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
23.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
Download
  • Mapping_APP(iOS_Android)
  • 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 PRO repository

1.MovelT2 configuration

MoveIt2 Configuration

Preface: Raspberry Pi 5 and Jetson Nano run ROS in Docker, so the performance of running MoveIt2 is generally poor. Users of Raspberry Pi 5 and Jetson Nano boards are advised to run MoveIt2 examples in a virtual machine. Orin motherboards run ROS directly on the motherboard, so users of Orin boards can run MoveIt2 examples directly on the motherboard, using the same instructions as running in a virtual machine. This section uses running in a virtual machine as an example.

1. Content Description

This section explains how to configure MoveIt2 and generate the parameter files and launch files required for simulation.

2. Introduction to MoveIt2

MoveIt 2 is the next generation of MoveIt , designed for ROS 2 (Robot Operating System 2) . It is an open-source framework for robot motion planning, manipulation, 3D perception, kinematics, collision detection, and mission planning. It is widely used in industrial robots, service robots, mobile manipulators, as well as in scientific research and education.

2.1. Differences from MoveIt

characteristicMoveItMoveIt2
ROS versionROS1ROS2
Real-timeLimited supportBetter real-time performance
Cross-platform supportMain LinuxSupports Linux, Windows, and macOS (ROS 2 feature)
Motion Planning InterfaceActionLib (ROS 1)Action (ROS 2)
Default plannerOMPLOMPL + More optimization options

2.2. MoveIt2 Core Functions

  • Motion Planning : Supports multiple planning algorithms (such as OMPL, CHOMP, STOMP, etc.) to generate collision-free motion trajectories.
  • Inverse Kinematics (IK) : Calculates the robot's joint angles to achieve the target pose.
  • Collision Checking : Real-time collision detection based on FCL (Flexible Collision Library) .
  • 3D Perception Integration : Supports point cloud and depth camera (such as RealSense, Kinect) data.
  • Manipulation : Provides a high-level interface for grabbing and placing objects.
  • Task Planning : Combines Behavior Trees for high-level task orchestration.

2.3. Install MoveIt2

MoveIt2 has been installed in the virtual machine, so there is no need to install it here. If you need to install MoveIt2 in a new environment, enter the following command to install it.

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#Change the <distro> below to your own ROS version. It is recommended to use humble (22.04) or Rolling (24.04)
sudo apt install ros-<distro>-moveit -y

2.4. Reference Websites

MoveIt2 source code:

GitHub - moveit/moveit2: 🤖 MoveIt for ROS 2

Official tutorial documentation:

MoveIt 2 Documentation — MoveIt Documentation: Humble documentation

3. Program startup

First, create a folder under the src folder of the ros workspace to store the files generated after MoveIt configuration. Taking the moveit2_ws workspace in the virtual machine as an example, enter the virtual machine terminal.

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cd moveit2_ws/src
mkdir test_config

Enter the following command in the virtual machine terminal to start MoveIt2 configuration,

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ros2 run moveit_setup_assistant moveit_setup_assistant

After the program starts, the following configuration screen appears.

image-20250620115118664

Click [Create New MoveIt Configuration Package] and the following screen will appear.

image-20250620115601046

Click [Browse] and select the M3Pro URDF file. The file directory is in /home/yahboom/moveit2_ws/src/yahboom_M3Pro_description/urdf. After selecting, click [Load Files]. The program will then load the selected URDF file. After loading, the following screen will appear, with the loaded M3Pro car model displayed on the right.

image-20250620115836220

Then click [Self-Collisions] in the left configuration bar. This step is to configure self-collision detection, as shown in the figure below. Click [Generate Collisions Matrix] to complete the configuration.

image-20250620120247614

Next, click [Planning Groups] in the left configuration bar. This step is to create a planning group. Click [Add Group] to create the first planning group, as shown below.

image-20250620120548047

Then create the arm_group planning group to control the robotic arm, as shown in the figure below.

image-20250620120854133

Then, we need to add this planning group. Click [Add Joints] below to enter the adding interface. In the adding interface, we select arm_Joint1 to arm_Joint5 on the left, click > to complete the addition, and click [Save] to save and exit.

image-20250620120959660

Complete the arm_group planning group settings as shown below, then click [Add Group] to add the planning group of the gripper.

image-20250620121244044

The parameters are shown in the figure below, then click [Add Links] to enter the Links selection interface.

image-20250620121358934

On the Links selection interface, select llink1, llink2, llink3, rlink1, rlink2, rlink3 on the left, click > to complete the addition, and then click [Save] to save and exit.

image-20250620121806203

The completed gripper planning group is shown in the figure below.

image-20250620121845971

At this point, the planning group settings are complete. Next, click [Robot Groups] in the left setting column. This step is to set the preset posture of the robot arm and gripper.

As shown in the figure below, click [Add Pose],

image-20250620122041247

Then set it as shown in the figure below, set the up posture of the arm_group planning group, the middle slider can set the posture, and the urdf on the right will also display the set posture. After the setting is completed, click [Save] to complete the setting.

image-20250620122215831

Next, we follow the steps to set the up posture, set the down posture and init posture of the arm_group planning group, and refer to the figure below for the settings.

Down posture:

image-20250620140850856

init posture:

image-20250620140958987

After setting the three postures of the arm_group group, set the two postures of the grip_group group to close and open. The main thing is that the [Planning Group] here needs to be changed to grip_group. The settings are as follows.

Close posture:

image-20250620141244979

Open posture:

image-20250620141329910

After setting up [Robot Poses], as shown below:

image-20250620141516004

Next, click [End Effectors] in the left setting column to configure the end effector, as shown in the figure below, and click [Add End Effector] to enter the setting interface.

image-20250620142020408

In the settings interface, make settings as shown in the figure below. After completing the settings, click [Save] to save and exit.

image-20250620142623114

The settings of [End Effectors] are as shown below.

image-20250620142714328

Next, click [ros2_control URDF Modifications] in the left setting column. This step is to set the URDF model. We do not need to modify the URDF model. Just click [Add interfaces], as shown below.

image-20250620143114727

Click [ROS2 Controllers] in the left setting column. This step is to set up the robot motion control. Click [Add Controller] to add a controller, as shown below.

image-20250620143726265

After entering the settings, add the arm_group_controller controller as shown below.

image-20250620143907324

Then click [Add Planning Group Joints] to add the joints of the control group, as shown in the figure below, add the arm_group control group, select the arm_group on the left and click > to complete the addition, and finally click [Save] to save and exit.

image-20250620144133413

The first controller after setting up is shown in the figure below.

image-20250620144305767

Then, we add a second controller. Click [Add Controller] to enter the add interface, and then set it up as shown in the figure below.

image-20250620144904389

Then click [Add Planning Group Joints] to add joints, as shown in the figure below, select grip_group on the left, and then click > to complete the addition. Finally, click [Save] to complete the setting.

img

After completing the [ROS2 Controllers] settings, as shown below,

image-20250620145344215

Next, click [MoveIt Controllers] in the left setting column. This step is to set the trajectory controller to execute the planned trajectory.

The trajectory is sent to the robot ROS2 controller. Click [Add Controller] to add a trajectory controller, as shown below.

image-20250620150250522

Enter the settings interface and set it up as shown below. Note that the [Controller Name] here should be the same as the [ROS2 Controller] set in the previous step, then click [Add Planning Group Joints] to add control joints.

image-20250620150407017

As shown in the figure below, add the arm_group control group, select arm_group on the left and click > to complete the addition, and finally click [Save] to save and exit.

image-20250620150614286

After the settings are completed, the following figure will be shown:

image-20250620150710212

Next, add the trajectory controller of the gripper. Click [Add Controller] to enter the settings interface. Set it up as shown in the figure below, and then click [Add Planning Group Joints] to add the control joints.

image-20250620151203479

Then click [Add Planning Group Joints] to add joints, as shown in the figure below, select grip_group on the left, and then click > to complete the addition. Finally, click [Save] to complete the setting.

image-20250620151732760

Complete the [MoveIt Controllers] settings as shown below.

image-20250620151814116

Next, click [Author Information] in the settings column on the left, and then fill in your name and email address, as shown below.

image-20250620151935855

Finally, click [Configuration Files] in the settings column on the left, click [Browse], find the folder we created earlier, select here /home/yahboom/moveit2_ws/src/test_moveit_config, and click [OK] when the following message appears

image-20250620152518443

Then click [Generate Package] below to generate the function package, as shown in the figure below. Click [OK] when the prompt message appears.

image-20250620152626993

When the prompt message appears, click [OK].

image-20250620152646396

As shown in the figure below, the Configuration package generated successfully appears . Click [Exit Setup Assistant] to complete all settings.

image-20250620152724263

In the test_moveit_config package, all the settings just made are saved. Then, we need to modify the joint_limits.yaml file in the /home/yahboom/moveit2_ws/src/test_moveit_config/config directory. We only need to change the integers in it to decimals, and the values remain unchanged. The modified file is as follows:

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# joint_limits.yaml allows the dynamics properties specified in the URDF to be overwritten or augmented as needed
​
# For beginners, we downscale velocity and acceleration limits.
# You can always specify higher scaling factors (<= 1.0) in your motion requests.  # Increase the values below to 1.0 to always move at maximum speed.
default_velocity_scaling_factor: 0.1
default_acceleration_scaling_factor: 0.1
​
# Specific joint properties can be changed with the keys [max_position, min_position, max_velocity, max_acceleration]
# Joint limits can be turned off with [has_velocity_limits, has_acceleration_limits]
joint_limits:
  arm1_Joint:
    has_velocity_limits: true
    max_velocity: 1.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  arm2_Joint:
    has_velocity_limits: true
    max_velocity: 1.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  arm3_Joint:
    has_velocity_limits: true
    max_velocity: 1.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  arm4_Joiint:
    has_velocity_limits: true
    max_velocity: 1.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  arm5_Joint:
    has_velocity_limits: true
    max_velocity: 1.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  llink1_Joint:
    has_velocity_limits: false
    max_velocity: 0.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  llink2_Joint:
    has_velocity_limits: false
    max_velocity: 0.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  llink3_Joint:
    has_velocity_limits: false
    max_velocity: 0.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  rlink1_Joint:
    has_velocity_limits: true
    max_velocity: 1.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  rlink2_Joint:
    has_velocity_limits: false
    max_velocity: 0.0
    has_acceleration_limits: false
    max_acceleration: 0.0
  rlink3_Joint:
    has_velocity_limits: false
    max_velocity: 0.0
    has_acceleration_limits: false
    max_acceleration: 0.0

Save and exit, then return to the workspace directory, use colcon build to compile, and enter in the terminal,

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cd moveit2_ws
colcon build --packages-select test_moveit_config

After the compilation is complete, refresh the environment variables and enter the terminal source ~/.bashrc. Then enter the following command in the terminal to start moveit2. Enter the terminal,

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ros2 launch test_moveit_config demo.launch.py

After the program is started, when the terminal displays "You can start planning now!" , it indicates that the program has been successfully started, as shown in the figure below.

image-20250620154038745

Then we test Plan and Execute. Let's test arm_grou first. As shown in the figure below, select [Planning Group] as arm_group, select [Start State] as、Select【Goal State】,We let the posture of the robot arm change from the current up ,motion planning to the previously set init,

image-20250620154420981

Then click [Plan & Execute] on the left to let the robot plan run to init, as shown in the figure below.

image-20250620154714153

After the motion planning is completed, as shown in the figure below,

image-20250620154624000

If the plan and execution are successful, it means that the arm_group configuration is successful. Next, test the grip_group. Set it as shown below, set [Planning Group] to grip_group, select [Start State] to、Select【Goal State】,

image-20250620155140888

Click [Plan & Execute] on the left to run the gripper planning to the close state, as shown in the figure below.

image-20250620155247804

If the gripper closes successfully, the plan is executed successfully.

4. Set up RVIZ

When running MoveIt2, the robot arm may repeat the planned operation. This is because the loop animation is enabled . To disable this option, go to [Display], find [MotionPlanning] -> [Planned Path] -> [Loop Animation], and click the √ here to disable the loop animation.

When running MoveIt2, the orange part represents the target pose. If we do not want to display the target pose, we can find [MotionPlanning]->[Query Goal State] and click the √ here to cancel the display of the target pose.

After modifying the rviz settings here, you need to press ctrl and s to save .

Medipipe gesture control robotic arm action group
MovelT2 simulation-reality linkage

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