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MicroROS V2 Robot Car📖
01.Introduction
  • 0.Unboxing Video
  • 1. Readme Learning Route
  • 2. Must Read Before Use
  • 3. Introduction to MicroROS V2 Control Board
  • 4. Introduction to LiDAR
  • 5. Introduction to ESP32 Camera Module
  • 6. FAQ
  • 7. About Charging
02.Assembly course
  • Assembly Video
03.Preparation
  • 1. Quickly Start
  • 2. Write Firmware
  • 3. Install VM and Start System
  • 4. Configure VM and Connect Robot
  • 5. Connect to MicroROS Agent
04.Quick start control course
  • 1. VM Keyboard Remote Control
  • 2. VM Handle Remote Control
  • 3. USB Handle Control
05.Robot control course
  • 1. Robot Information Release
  • 2. Robot Keyboard Control
  • 3. Robot Handle Control
  • 4. Robot State Estimation
  • 5. Linear Speed Calibration
  • 6. Angular Velocity Calibration
  • 7. Robot URDF Model
06.Lidar course
  • 1. Precautions for LiDAR Mapping and Navigation
  • 2. Lidar Avoid
  • 3. Lidar Following
  • 4. Lidar Guard
  • 5. Lidar Patrol
  • 6. Gmapping Mapping
  • 7. Cartographer Mapping
  • 8. Cartographer Quickly Repositioning Navigation
  • 9. Slam Toolx Mapping
  • 10. Navigation2 Single Point Navigation
  • 11. Navigation2 Multi Point Navigation
  • 12. Ros Robot App Mapping And Navigation
07.Road network planning
  • 1. Introduction to Road Network Planning and Quick Start
  • 2. Build a Pose Map
  • 3. Road Network Annotation
  • 4. Planning and Navigation Between Road Networks
  • 5. Road Network Navigation in Any Pose
  • 6. Path Replanning
08.Vision basic course
OpenCV Image Processing
  • 1. Introduction to OpenCV 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
09.Visual General Course (For Standard&Superior version)
4. Yolov11&26 Visual Recognition
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Prediction
1. ESP32 Visual Recognition Module Configuration
  • 1. Serial Port Configuration WiFi Instructions
  • 2. Use ESP32 Camera Module in Robot Car
  • 3. Servo PTZ Calibration
2. OpenCV Visual Recognition
  • 1. Human Pose Estimation
  • 2. Object Detection
  • 3. AR Vision
  • 4. QR Code
  • 5. Color Recognition
  • 6. Facial Recognition
  • 7. AprilTag Machine Code Recognition
3. Mediapipe Visual Recognition
  • 1. Hand Detection
  • 2. Pose Detection
  • 3. Holistic Detection
  • 4. Facial Detection
  • 5. Facial Recognition
  • 6. Facial Special Effects
  • 7. 3D Object Recognition
  • 8. Brush
  • 9. Gesture Recognition
  • 10. Palm Target Localization
  • 11. Fingertip Trajectory Recognition
10.Visual Advanced Course (Just for Standard version)
1. Visual Control
  • 1. QR Code Recognition Control Action
  • 2. AprilTag Control Car Action Group
  • 3. Gesture Control Car Action Group
  • 4. Visual Line Tracking
2. Visual Tracking
  • 1. Color Tracking
  • 2. Facial Tracking
  • 3. QR Code Tracking
  • 4. Object Recognition And Tracking
  • 5. Mediapipe Palm Tracking
  • 6. Mediapipe Gesture Tracking
  • 7. Mediapipe Human Pose Tracking
  • 8. KCF Object Tracking
  • 9. AprilTag Machine Code Tracking
3. Visual Following
  • 1. Color Follow
  • 2. Face Follow
  • 3. QR Code Follow
  • 4. Mediapipe Palm Follow
  • 5. Mediapipe Gesture Follow
  • 6. Mediapipe Human Posture Follow
  • 7. AprilTag Machine Code Follow
  • 8. Object Follow
11.Visual Advanced Course (Just for Superior version)
1. Visual Control
  • 1. QR Code Recognition Control Action
  • 2. AprilTag Control Car Action Group
  • 3. Gesture Control Car Action Group
  • 4. Visual Line Tracking
2. Visual Tracking
  • 1. Color Tracking
  • 2. Facial Tracking
  • 3. QR Code Tracking
  • 4. YOLO Object Recognition and Tracking
  • 5. Mediapipe Palm Tracking
  • 6. Mediapipe Gesture Tracking
  • 7. Mediapipe Human Pose Tracking
  • 8. KCF Object Tracking
  • 9. AprilTag Machine Code Tracking
3. Visual Follow
  • 1. Color Follow
  • 2. Face Follow
  • 3. QR Code Follow
  • 4. Mediapipe Palm Follow
  • 5. Mediapipe Gesture Follow
  • 6. Mediapipe Human Pose Follow
  • 7. AprilTag Machine Code Follow
  • 8. Object Follow
12.AI Large Model Basic and Applications Course
1. AI Large Model Preparation
  • 1.AI Large Model Preparation
2. AI Large Model Basic Course
  • 1. AI Large Model Types and Principles
  • 2. RAG Retrieval Augmented and Training Samples
  • 3. Embodied Intelligent System Architecture
  • 4. Embodied Intelligence Core Source Code
3. AI Large Model Development
  • 1. Register Model Service Account
  • 2. Configure API KEY
  • 3. Dify Introduction
  • 4. Dify Basic Features
  • 5. RAG Knowledge Base Deployment
  • 6. AI Application Development Chatbot
  • 7. RAG Knowledge Base and Chatbot
  • 8. AI Agent Workflow
4. AI Large Model (Text Version)
  • 1. Semantic Understanding and Instruction Following
  • 2. Multimodal Visual Understanding
  • 3. Multimodal Visual Understanding + Basic Control
  • 4. Multimodal Visual Understanding + Object Following
  • 5. Multimodal Visual Understanding + Visual Line Following
  • 6. Multimodal Visual Understanding + SLAM Navigation
  • 7. Multimodal Visual Understanding + SLAM Navigation + Visual Line Following
  • 8. Multimodal Visual Understanding + SLAM Navigation + Object Following
  • 9. Intent Inference + Multimodal Visual Understanding + SLAM Navigation
13.Openclaw Basics Course
  • 1. Openclaw Introduction
  • 2. Openclaw Core Concepts
  • 3. Openclaw Api-Key Configuration
  • 4. Openclaw Switching Models
  • 5. Openclaw System Prompt
  • 6. Openclaw Common CLI Command
14. Openclaw Interaction Course
  • 1. Openclaw Webchat Interaction
  • 2. Openclaw Tui Interaction
  • 3. Openclaw Whatsapp Interaction
15.Openclaw Development Course
  • 1. Openclaw Robot Mcp Service Integration
  • 2. Robot CLI Command Tools
  • 3. Robot-Control Plugin Tools
  • 4. Openclaw Skills Development
  • 5. Openclaw Scheduled Tasks
  • 6. Openclaw Multi Agent System
  • 7. Openclaw Proactive Interaction
  • 8. Openclaw Vector Memory
16.Openclaw Embodied Intelligence Course
  • 1. OpenClaw Natural Interaction + Basic Control
  • 2. OpenClaw Natural Interaction + Slam Navigation
  • 3. OpenClaw Natural Interaction + Multimodal Visual Understand
  • 4. OpenClaw Natural Interaction + Multimodal Visual Understand + Slam Navigation + Visual Follow
  • 5. OpenClaw Natural Interaction + Multimodal Visual Understand + Slam Navigation + Visual Track
17.Multi-machine Course
  • 1. Multi Machine Handle Control
  • 2. Multi Machine Keyboard Control
  • 3. Multi Machine Navigation
18.MicroROS-V2 Control Board Development Environment
  • 1. Set Up the ESP32-IDF Development Environment
  • 2. ESP32-IDF Configuration Tool
  • 3. ESP Flash Tool Flashing Firmware
  • 4. Install ESP32 Microros Components
  • 5. Install And Start Microros Agent
19.MicroROS-V2 Control Board ESP32 Basic Course
  • 1. Led Light Up
  • 2. Button Function
  • 3. Drive Buzzer
  • 4. Oled
  • 5. Usb Host Function
  • 6. Serial Communication
  • 7. Battery Voltage Detection
  • 8. Drive Pwm Servo
  • 9. Drive Motors
  • 10. Read Motor Encoder Data
  • 11. Pid Motor Speed Control
  • 12. Robot Kinematics Analysis Theory
  • 13. Read Imu Data
  • 14. Read Lidar Data
  • 15. Flash Data Storage
  • 16. Custom Partition Table
  • 17. Bluetooth Communication
  • 18. Wifi Connection
  • 19. ESP32 Visual Recognition Module
20.MicroROS-V2 Control Board Micro_ros Basic Course
  • 1. Publish Topics
  • 2. Subscribe To Topics
  • 3. Multi Topic Subscription And Publishing
  • 4. Subscribe To Buzzer Topic
  • 5. Subscribe To Pwm Servo Topic
  • 6. Subscribe To Speed Control Topic
  • 7. Publish Odometry Topic
  • 8. Publish Imu Data Topic
  • 9. Publish Lidar Data Topic
21. 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
22.Docker Course
  • 1.Docker overview and docker installation
  • 2.Common commands for docker image containers
  • 3.Docker images deeply understand and publish images
23.ROS 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)
  • Code
  • Software_Tools
  • VM_System_File
  • 3D_Model_File
  • ESP32_Firmware
  • Dify LLM Base
  • Instruction_Manual
  • VMware
Download ZIP

Welcome to MicroROS V2 Robot Car repository

1. Readme Learning Route

User Manual

User Manual1. Battery Charging Notes1.1 Low Battery Voltage Threshold Alarm1.2 Battery Charging2. First-Time Usage Steps2.1 Assemble the Robot Car2.2 Download the Virtual Machine Image2.3 Configure the Virtual Machine to Connect to the Robot3. Viewing the Source Code3.1 Viewing and Editing Source Code with Visual Studio Code3.2 Directory Structure Description3.3 Symbol Conventions3.4 How to Build ROS Packages

1. Battery Charging Notes

1.1 Low Battery Voltage Threshold Alarm

  • When the battery voltage drops below the threshold (10.2V), the buzzer will emit a beep—beep—beep alarm. At this point you should charge the battery using the charger. Click the button on the right to switch to the BATTREY_INFO panel to view the current battery voltage and the voltage threshold.

image-20260803150731664

1.2 Battery Charging

  • Connect the charger provided with the product to the power jack; the charger indicator light turns green

image-20260803145810473

  • Turn off the robot power, then connect the charger plug to the charging port on the controller board

image-20260803145916765

 

  • During charging, the charger indicator light is red; once the battery is fully charged, the indicator turns green

image-20260803150001725

 

2. First-Time Usage Steps

  • Follow the steps below to complete basic configuration such as robot assembly and virtual machine installation

2.1 Assemble the Robot Car

  • Refer to [2. Assembly Tutorial] to complete the assembly of the robot car

image-20260803151809881

2.2 Download the Virtual Machine Image

  • Refer to the tutorial document [Preparation - Install VM and Start System] to download the virtual machine image provided with the product. The image file is located in the [Virtual Machine Image] folder of the supporting materials

 

2.3 Configure the Virtual Machine to Connect to the Robot

  • Refer to the tutorial document [Preparation - Configure VM and Connect Robot], and use the RobotManager tool in the virtual machine to complete basic configuration such as the robot model, microROS agent address, and camera IP

 

3. Viewing the Source Code

[!NOTE]

  • Visual Studio Code is a lightweight, efficient, and extensible tool with integrated core development features at its heart, making it one of the most popular development tools in the world
  • Official website: https://code.visualstudio.com/. If you have not installed Visual Studio Code, you can search for the official website and download and install it

3.1 Viewing and Editing Source Code with Visual Studio Code

 

  • Launch Visual Studio Code, click the Extensions icon on the left, and install three remote connection plugins: Remote-SSH, Remote - SSH: Editing Configuration Files, and Remote Explorer

image-20260107173441245

  • Then click Remote Explorer on the left, and click New Remote

image-20260107174218199

 

  • In the pop-up input box, enter username@IP-address for your board, press Enter, then enter the user password yahboom to log in to the robot car

image-20260803143154675

 

  • Then click Open Folder; in the pop-up window you can select the folder you want to view. Here, select microros_ws as an example, then click OK

image-20260803143950565

  • The code workspace directory structure is as follows

3.2 Directory Structure Description

  • 📁 src/ — Source code directory, containing the source code of all ROS 2 packages; it is the main development area of the entire workspace:
Package nameFunction
interfaces/Custom message/service/action interface definitions (msg, srv, action)
microros_v2_bringup/Robot launch package: launch files, config files, rviz visualization configuration
microros_v2_opencv_visual_pkg/OpenCV vision processing nodes
microros_v2_opencv_base_pkg/OpenCV basic tutorial scripts (geometric transforms, image enhancement, drawing, etc.)
microros_v2_yolo_pkg/YOLO object detection related nodes
yolo_onnx_follow_pkg/Vision following based on the YOLO ONNX model
microros_v2_kcf_follow_pkg/KCF target tracking and following
microros_v2_mediapipe_pkg/MediaPipe human body/gesture perception features
microros_v2_ptz_visual_control_pkg/Pan-tilt (PTZ) vision control
microros_v2_no_ptz_visual_control_pkg/Vision control for the version without a pan-tilt
multi_brains/, multi_brains_pre/Multi-"brain" decision/task planning modules (including LLM/Dify integration related configs)
roadnet/Road network/navigation related (C++ package, containing graph data graphs)
robot_description/Robot URDF model description
robot-control/, ros_robot_app/Robot control and application layer
common_demo/Common example code
scripts/, robot_config/Helper scripts and robot configuration
  • 📁 build/ — Build intermediate artifacts

Intermediate files generated during colcon compilation (CMake cache, object files, etc.), can be deleted and regenerated by rebuilding.

  • 📁 install/ — Build installation output

The installation directory after colcon compilation, containing executables, libraries, Python packages, and launch files. After running source install/setup.bash, you can use the nodes and commands compiled here.

  • 📁 python_env/ — Python virtual environment

An independent Python environment managed by uv, to prevent vision-related dependencies (such as onnxruntime, mediapipe, etc.) from polluting the system environment:

  • mircoros_v2_env/ — main project Python environment, yolo_env/ — YOLO dedicated environment
  • 📁 third_party_library/ — Independent workspace for third-party libraries

An independent colcon workspace dedicated to compiling and installing third-party SLAM-related libraries (cartographer, cartographer_ros, slam_gmapping, openslam_gmapping), isolated from the main workspace for easier maintenance.

  • 📁 cache/ — Runtime cache

Cache files generated during program runtime, such as debug images (llm_camera.jpg, grid_images.png), YOLO model inference verification images (bus_predict_yolo11n/), etc.

 

3.3 Symbol Conventions

  • In the subsequent tutorial documents, the $HOME and ~ symbols represent the user home directory /home/yahboom. For example:

$HOME/microros_ws/src/microros_v2_bringup/microros_v2_bringup/visual_track.py is equivalent to /home/yahboom/microros_ws/src/microros_v2_bringup/microros_v2_bringup/visual_track.py

image-20260803155819095

 

3.4 How to Build ROS Packages

Quick Method

  • Press ctrl+shift+B in the Visual Studio Code interface, and a build selection panel will pop up. When building a normal package, select Build Package

image-20260803160231019

  • Select the package you want to build from the pop-up list

image-20260803160130595

 

  • When building microros_v2_bringup and robot_description, select Build Package. In subsequent use, modifications to the launch files and configuration in microros_v2_bringup will take effect directly, without needing to rebuild the package

image-20260803155916263

 

Manual Build Method

cd ~/microros_ws/
colcon build --packages-select <package_name>
  • Example

image-20260803160641022

Unboxing Video
Must Read Before Use

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