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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

16.Mobile App Mapping And Navigation

App Mapping and Navigation

App Mapping and Navigation1. Course Content2. Preparation4. App Mapping Case5. App Navigation Case6. Source Code Analysis

1. Course Content

Control the car's mapping and navigation through the mobile app 【ROS Robot】.

2. Preparation

  1. Your phone needs to first download the 【ROS Robot】 app. Android/iOS phone users, please scan the QR code to download the remote control software. iOS users can also search for and download the mapping and navigation app 【ROSRobot】 in the App Store.

image-20250702142850792

  1. Then the car and the phone must be on the same local area network; this can be achieved by connecting to the same Wi-Fi.

 

4. App Mapping Case

  • Enter the following command in the car's terminal to start the car's app mapping service node

xxxxxxxxxx
ros2 launch yahboomcar_bringup bringup_app.launch.py
  • Open 【ROS Robot】, which displays as shown below

  • Enter the car's IP address ——> ROS2 ——> VideoTopic/camera/rgb/image_raw/compressed ——> 【Connect】

cf6a7e8e27588ac943936de48fe6999b

 

  • After successfully connecting, it displays as follows

 

  • Use the sliding wheel to control the car to slowly move through the area to be mapped, then click Save Map, enter a map name and click Submit to save the map

 

  • The map will be automatically saved in the system's ~/map directory, and the terminal will indicate that the map was saved successfully

image-20251210105159576

 

 

5. App Navigation Case

xxxxxxxxxx
ros2 launch yahboomcar_bringup bringup_app.launch.py navigation_mode:=True 

Note

Optional parameter description

  • map_file

    • Map file path; here the map yaml name is required; the default value is map.yaml

 

  • Open 【ROS Robot】, which displays as shown below

  • Enter the car's IP address ——> ROS2 ——> VideoTopic/camera/rgb/image_raw/compressed ——> 【Connect】

 

  • As shown below, select the navigation interface:

 

  • Then, based on the car's actual pose, click 【Set Initial Pose】 to give the car an initial pose. If the area scanned by the LiDAR roughly overlaps with the actual obstacle, it means the pose is accurate. As shown below,

 

  • Click 【Set Navigation Point】 to give the car a destination; the car will plan a path and move to the destination along the path. As shown below:

 

 

6. Source Code Analysis

Launch and backend service source code paths:

xxxxxxxxxx
~/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_bringup/launch/bringup_app.launch.py
xxxxxxxxxx
~/yahboomcar_ros2_ws/yahboomcar_ws/src/ros_robot_app/ros_robot_app/

 

  • The key startup program is as follows:

  • The program uses the two launch parameters slam_mode and navigation_mode to decide between the two startup modes of mapping or navigation, and starts the rosbridge WebSocket server to transmit relevant data through the WebSocket protocol.

    slam_mode=LaunchConfiguration('slam_mode', default="slam_toolbox")
    navigation_mode=LaunchConfiguration('navigation_mode', default="False")


    #gmapping
    gmapping_launch=IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(yahboomcar_bringup_dir,
                        'launch',
                        'gmapping.launch.py')),
        launch_arguments={
                        "rviz": "False",
                         }.items(),
        condition=IfCondition(PythonExpression(["'", slam_mode, "' == 'gmapping' and '", navigation_mode, "' == 'False' "]))
    )
    #slam_toolbox
    slam_toolbox_launch=IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(yahboomcar_bringup_dir,
                        'launch',
                        'slam_toolbox.launch.py')),
        launch_arguments={
                        "rviz": "False",
                         }.items(),
        condition=IfCondition(PythonExpression(["'", slam_mode, "' == 'slam_toolbox' and '", navigation_mode, "' == 'False' "]))
    )

    #Start Cartographer mapping mode.
    cartographer_launch=IncludeLaunchDescription(
        PythonLaunchDescriptionSource(os.path.join(yahboomcar_bringup_dir,
                        'launch',
                        'cartographer.launch.py')),
        launch_arguments={
                        "rviz": "False",
        }.items(),
        condition=IfCondition(PythonExpression(["'", slam_mode, "' == 'cartographer' and '", navigation_mode, "' == 'False' "]))
        
        )

    #Start the rosbridge node.
    bringup_rosbridge_server = ExecuteProcess(
        cmd=['ros2', 'launch', 'rosbridge_server', 'rosbridge_websocket_launch.xml'],
        output='screen'
    )

    transmission_node = Node(
            package='ros_robot_app',
            executable='transmission',
            name='transmission',
            parameters=[
                {'rgb_topic': GetCameraRgbTopic()},
                {'flip_laser_points': flip_laser_points}
            ],
            output='screen',
    )


    #Robot pose publishing node
    robot_pose_publisher=Node(
        package="ros_robot_app",
        executable="robot_pose_publisher",
        name="robot_pose_publisher",
        output="screen",
        parameters=[
                {"use_sim_time": False},
                {"is_stamped": True},
                {"map_frame": "map"},
                {"base_frame": "base_link"}
        ]
    )
    
    #App map saving service node
    app_save_map_node = Node(
        package='ros_robot_app',
        executable="app_save_map",
        name="app_save_map",
        output="screen",
    )

    app_nav= IncludeLaunchDescription(
                PythonLaunchDescriptionSource(os.path.join(yahboomcar_bringup_dir, 
                                    "launch",
                                    'nav2.launch.py')),
                launch_arguments={
                    "map": LaunchConfiguration("map_file"),
                    "rviz": "False",
                    "localization_mode": "amcl",
                    "slam": "False",
                }.items(),
                condition=IfCondition(PythonExpression(["'", navigation_mode, "' == 'True'" ]))
            )

    return LaunchDescription([
        *declared_arguments,
        bringup_camera,
        app_nav,                                #app navigation node
        bringup_rosbridge_server,               #rosbridge
        transmission_node,                      #publish rgb image and laser scan point
        robot_pose_publisher,                   #robot pose publishing node
        gmapping_launch,                        #gmapping slam 
        slam_toolbox_launch,                    #slam_toolbox slam
        cartographer_launch,                    #cartographer slam
        app_save_map_node
    ])
Aruco Visual Relocalization Navigation
USB Camera Introduction

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