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ROSMASTER M1 PRO📖
0.Robot Configuration and Operation Guidelines
  • 0.Unboxing and Review
  • 1.Assembly Videos
  • 2.User Manual
  • 3.Enter Docker (For Raspberry Pi)
  • 4.FAQ
  • 5.RobotManager User Guide
1.Chassis Control Course
  • 1.Robot Information Publishing
  • 2.Robot Handle Control
  • 3.Robot Keyboard Control
  • 4.Linear Velocity Calibration
  • 5.Angular Velocity Calibration
  • 6.Robot URDF Model
  • 7.Robot EKF State Estimation
2.Lidar Course
  • 1.Lidar Introduction And Use
  • 2.Lidar Obstacle Avoidance
  • 3.Lidar Following
  • 4.Lidar Guard
  • 5.Lidar Patrol
  • 6.GMapping-SLAM Mapping
  • 7.Cartographer-SLAM Mapping
  • 8.Slam-Toolbox Mapping
  • 9.Lifelong Mode Mapping
  • 10.Navigation2 Single Point Navigation
  • 11.Navigation2 Multi Point Navigation
  • 12.Cartographer Relocalization Navigation
  • 13.Slam-Toolbox Localization Navigation
  • 14.Synchronous Mapping And Navigation
  • 15.Aruco Visual Relocalization Navigation
  • 16.Mobile App Mapping And Navigation
3.USB Camera-Depth Camera Course
  • 1.USB Camera Introduction
  • 2.USB Camera Intrinsic Calibration
  • 3.Nuwa-HP60C Camera Introduction (Depth Camera Only)
  • 4.Depth Pseudo Color Image (Depth Camera Only)
  • 5.Depth Camera Distance Measurement (Depth Camera Only)
  • 6.Block Volume Calculation (Depth Camera Only)
  • 7.Edge Detection (Depth Camera Only)
  • 8.RTAB-Map SLAM Mapping (Depth Camera Only)
  • 9.RTAB-Map Navigation (Depth Camera Only)
4.Robotic Arm and 3D Space Gripping Course
  • 1.Robotic Arm Basic Usage
  • 2.Robotic Arm Kinematics
  • 3.Robotic Arm Chassis Coordination Control
  • 4.AprilTag ID Sorting
  • 5.AprilTag Height Anomaly Sorting
  • 6.AprilTag Tracking and Grasping
  • 7.Color Block Sorting
  • 8.Color Block Height Anomaly Sorting
  • 9.Color Block Tracking and Grasping
  • 10.Wood Block Shape Sorting
  • 11.KCF Tracking and Grasping Objects
  • 12.Mediapipe Gesture ID Sorting AprilTag
  • 13.Mediapipe Gesture Height Sorting AprilTag
  • 14.Desktop Tracking and Grasping AprilTag
  • 15.3D Spatial Tracking AprilTag
  • 16.Transformer Model Tracking Algorithm
  • 17.Line Following Obstacle Clearing
5.Road network planning and navigation
  • 1.Introduction To Road Network Planning
  • 2.Road Network Annotation
  • 3.Planning And Navigation Between Waypoints
  • 4.Road Network Navigation In Any Pose
  • 5.Path Re-planning
6.OpenClaw Basic Course
  • 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 Method
  • 1.OpenClaw Webchat Interaction
  • 2.OpenClaw Tui Interaction
  • 3.OpenClaw Voice Dialogue Interaction
  • 4.OpenClaw WhatsApp Interaction
8.OpenClaw Development
  • 1.OpenClaw Connecting to Robot MCP Service
  • 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 Scheduled Tasks
  • 10.OpenClaw Multi-Agent Intelligent Agent
  • 11.OpenClaw Active Interaction
  • 12.OpenClaw Vector Memory
9.OpenClaw Embodied intelligent application
  • 1.OpenClaw Target Tracking
  • 2.OpenClaw Arm Tracking And Grasping
  • 3.OpenClaw Arm Fixed-point Placement
  • 4.OpenClaw Waste Sorting
  • 5.OpenClaw SLAM Mapping And Navigation
  • 6.OpenClaw Navigation Transport
  • 7.OpenClaw AprilTag Grasping
  • 8.OpenClaw Color Line Patrol
  • 9.OpenClaw Visual Distance Measurement
10.OpenClaw scenario sandbox
  • 1.Map Description and Props Placement
  • 2.Building the Sandbox Map
  • 3.Visual Relocalization Marker
  • 4.Map Mapping Marker
  • 5.Sandbox Scenario Comprehensive Case
11.AI Large 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 large Model Development
  • 1.Register a Model Service Provider Account
  • 2.Configuring API-KEY
  • 3.Introduction to Dify
  • 4.Basic Dify Features
  • 5.AI Large Model Development - Chatbot
  • 6.Deploy the RAG Knowledge Base
  • 7.RAG Knowledge Base + Chatbot
  • 8.AI Agent Workflow
  • 9.Custom Wake-up Response
13.AI Model - Voice Version
  • 1.Semantic Understanding and Command Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding and Robotic Arm Gripping
  • 4.Multimodal Visual Understanding and SLAM Navigation
  • 5.Robotic arm gripping+Multimodal visual understand+SLAM navigation
  • 6.Intention Understanding
14.AI Model - Text Version
  • 1.Semantic Understanding and Command Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding and Robotic Arm Gripping
  • 4.Multimodal Visual Understanding and SLAM Navigation
  • 5.Robotic arm gripping+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
  • 10.3D perception obstacle‑avoidance
17.Multi-vehicle Course
  • 1.Multi-vehicle Control
  • 2.Multi-vehicle Navigation
  • 3.Multi-vehicle Formation
18.YOLO26 Development
  • 1.CLI Use
  • 2.Object Detection
  • 3.Instance Segmentation
  • 4.Pose Estimation
  • 5.Image Classification
  • 6.Oriented Object Detection
  • 7.YOLOv26 + DeepSORT Tracking
  • 8.Monocular Depth Estimation
19.Control Board STM32 Driver Course
  • 0.Notes (Must Read)
  • 1.About Expansion Board
  • 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
  • 14.1 Kinematic Analysis of Mecanum Wheel
  • 14.2 Kinematic Analysis of Ackerman
  • 14.3 Kinematic Analysis of 4WD
  • 15.PID Control Robot Movement
20.Docker Course
  • 1.Docker Introduction and Installation
  • 2.Docker Basic Commands
  • 3.Docker Submission and Multi-Terminal Access
  • 4. Docker Startup Script
  • 5.Docker-Vscode Environment Construction
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
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
24.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
  • 18. Controlling RGB Cooling Fans
Download
  • System File
  • Code
  • 3D Model File
  • Software Tools
  • Hardware_Info
  • Deb function package
  • Dify AI Agent
Download ZIP

Welcome to ROSMASTER M1 PRO repository

2.Road Network Annotation

Road Network Description File Annotation

Road Network Description File Annotation1. Course Content2. Preparation2.1 Starting the Road Network Annotation Program3. Road Network Annotation Case Demonstration3.1 Adding Waypoints3.2 Adding Edges4. Saving the Road Network Description File5. Loading and Modifying the Road Network Description File5.1 Loading the Road Network Description File5.2 Editing the Road Network

1. Course Content

  • Use the route_tool utility to annotate the road network and generate a .geojson file that describes the road network

2. Preparation

  • Refer to the LiDAR chapter 【Slam-Toolbox Mapping】 to build a grid map and a pose graph format pose map. After mapping is complete, the $HOME/map folder should contain the following 4 files:

image-20260831201807998

 

2.1 Starting the Road Network Annotation Program

  • Method 1: Start via RobotManager

image-20260831214521737

 

  • Method 2: Start via the CLI command line

ros2 launch yahboomcar_bringup nav2.launch.py rviz_config:=roadnet_edit localization_mode:=slam_toolbox
  • RViz will display the map and two coordinate frames, where map is the map coordinate frame, and base_footprint is the coordinate frame of the projection point on the ground at the center of the robot's chassis. Through base_footprint, we can know the robot's exact position in the map in real time.

image-20251119154122493

 

3. Road Network Annotation Case Demonstration

3.1 Adding Waypoints

  • Click the Publish Point tool in the RViz toolbar to enter the waypoint selection state

image-20251119154746850

 

  • Then left-click the mouse at the small blue dot at the center of the base_footprint coordinate frame. The position field under the Route Tool tab at the lower left will automatically fill in the coordinates of the current point, and then click Create to create a waypoint.

image-20251119155618408

image-20251119155909004

 

  • Next, we move the robot to the next position where a waypoint needs to be marked. What is demonstrated here is directly carrying the robot to the next position where a waypoint needs to be marked.

Tip

Here the robot can be moved by keyboard control, joystick control, or 2D Goal Pose navigation in RViz, or it can even be carried directly to the next position to be marked, because the pose map allows the robot's global position to be quickly and accurately localized.

 

  • As you can see, because the robot was moved directly, the global localization is lost, and the LiDAR contour no longer matches the map's environmental features. Here we can use the pose map to perform fast relocalization.

image-20251119160522893

 

  • Click the 2D Pose Estimate tool in the RViz toolbar

image-20251119160806879

 

  • Then give an estimated position near the robot's approximate position

image-20251119161316319

 

  • After that, the robot's exact localization in the global map will be restored immediately

Tip

  • The principle of this fast relocalization is to use slam_toolbox pure localization and the pose map to perform fast scan-map matching.

  • Note: During the waypoint marking process, if you observe that the LiDAR contour deviates from the map's environmental features (cumulative odometry error, wheel slip, manual movement, and various other factors can all cause local localization errors), you can use this method to quickly restore the robot's exact localization.

image-20251119161432015

 

  • Repeat the above steps until all the waypoints that need to be marked are completed (mark waypoints according to the user's own actual needs)

  • After marking is complete, you can first turn off TF and LaserScan on the left to check the waypoints

image-20251119164644188

 

3.2 Adding Edges

  • Select Edge in the Route Tool tab

image-20251119164954041

 

  • Fill in the starting waypoint of the edge in Start Node ID, fill in the ending waypoint of the edge in End Node ID, and then click Create to create an edge between the waypoints.

Important

Note!

The road network is a topological structure composed of points and edges, and edges have direction. For example, the edge from 0→1 created here is one-way. If a two-way edge is needed, an edge from 1→0 must also be created.

image-20251119165301086

  • After that, we create the edge from 1-0 so that waypoints 0 and 1 can be traveled in both directions.

image-20251119165823886

 

  • Repeat the above steps to complete the creation of all edges (whether an edge is set as one-way or two-way is determined by the actual scenario requirements). In this case demonstration, all are set as two-way edges.

image-20251119170355515

 

4. Saving the Road Network Description File

  • Click save in the Route Tool tab, then select the path where the file is to be saved in the pop-up window. Here it is saved in the $HOME/map/ folder.

image-20251119170801118

  • Then fill in the file name in File name. It is recommended to keep it consistent with the grid map name for easy distinction; the file extension must be .geojson. Finally, click save to save the road network description file.

image-20251119171231643

  • After a successful save, the terminal will print a prompt message

image-20251119171617353

  • After that, we can directly view the map.geojson road network description file from the host computer's $HOME/map folder. The file contains a JSON-format description of the waypoint and edge information.

image-20251119171821642

 

5. Loading and Modifying the Road Network Description File

5.1 Loading the Road Network Description File

  • If the previous road network description file needs to be modified later, for example to add, remove, or edit points and edges, you can load the previous road network description file for editing.

xxxxxxxxxx
ros2 launch yahboomcar_bringup nav2.launch.py rviz_config:=roadnet_edit localization_mode:=slam_toolbox
  • The yaml_filename parameter is the path of the grid map file of the road network to be annotated

 

image-20251119174818105

image-20251119175057600

 

5.2 Editing the Road Network

  • If you need to add new waypoints and edges, the operation is the same as the previous steps.

  • Click Edit to re-edit the information of an existing waypoint or edge.

image-20251119175320402

  • Click Remove to remove an existing waypoint or edge.

image-20251119175754294

Introduction To Road Network Planning
Planning And Navigation Between Waypoints

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