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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

2. Robot CLI Command Tools

Robot CLI Command Tools

Robot CLI Command Tools1. Course ContentCourse OverviewLearning Objectives2. Preparation3. Introduction to CLI Tools4. CLI Command Robot Control Communication Architecture5. Controlling the Robot with CLI5.1 CLI Command Summary5.2 Tools Supported by Different Vehicle Versions5.3 Command Format6. Demo Cases7. Source Code Analysis

1. Course Content

Course Overview

  • This lesson explains the use of the robot CLI (Command Line Interface) command tools. Through the command line interface, users can directly control various functions of the robot, such as chassis movement and visual recognition.
  • The CLI command tools encapsulate all MCP Tool interfaces. Without relying on an AI model, you can quickly control the robot, which is convenient for functional testing and debugging.

Learning Objectives

  1. Understand the functional positioning and application scenarios of the robot CLI command tools
  2. Become familiar with the functions, parameters, and usage format of CLI commands

[!IMPORTANT]

The demo in this lesson uses the pan-tilt camera version (PTZ) as an example; the MCP and CLI tool types may differ slightly across different vehicle versions

2. Preparation

ros2 launch microros_v2_bringup openclaw_service.launch.py

image-20260724111048244

 

3. Introduction to CLI Tools

The robot CLI (Command Line Interface) control tool is a command-line-based robot control interface that calls the various robot control tools registered on the MCP server through the robot_control command. It encapsulates the robot's underlying control interfaces, converting complex ROS2 communication into concise command-line instructions. You only need to enter a command in the terminal to control the robot to perform various actions.

image-20260429154300672

 

4. CLI Command Robot Control Communication Architecture

xxxxxxxxxx
                                                        ┌─────────────┐
                                                        │  CLI tool   │
                                                        └──────┬──────┘
                                                               │MCP protocol
                                                               ▼
                                                        ┌─────────────┐
                                                        │  MCP Server │
                                                        └──────┬──────┘
                                                               │
                                                               ▼
                                                        ┌─────────────┐
                                                        │ ROS2 Stack  │
                                                        │Topic/Service│
                                                        └──────┬──────┘
                                                               │
                                                               ▼
                                                        ┌─────────────┐
                                                        │   Hardware  │
                                                        │   Driver    │
                                                        └──────┬──────┘
                                                               │
                                                               ▼
                                                        ┌─────────────┐
                                                        │  Robot HW   │
                                                        └─────────────┘

 

5. Controlling the Robot with CLI

5.1 CLI Command Summary

You can view the list of all available CLI commands with robot_control list-tools. The following is a summary of all currently registered CLI commands:

CommandParametersFunction
Move--direction, --distance, --angleMove the robot chassis by a specified distance or rotate by a specified angle. direction options: forward, backward, turn_left, turn_right
SeeWhatNoneCapture one frame of image and return the saved path
AdjustCameraView--pitch, --yawAdjust the camera view. pitch controls tilt (positive = up, negative = down), yaw controls pan (positive = right, negative = left); a step of 5-10 degrees is recommended
GetBbox--queryDetect and return the bounding box (bbox) coordinates of the target object based on a text description
TargetTrack--x1-or-cmd, --y1, --x2, --y2Visual tracking of the target object. Pass cancel to stop tracking
FollowLine--colorFollow a colored route on the ground. color options: red, green, blue, yellow
CameraActionGroup--action_nameExecute camera preset action groups. Options: init_camera_pose, nod, shake
Navigation--locationNavigate to a target location; the parameter is the location symbol in the map mapping file
RecordMapLocation--name, --symbolSave the current location to the map mapping file
GetMapMappingNoneGet the mapping relationship between all location names and their corresponding symbols

5.2 Tools Supported by Different Vehicle Versions

  • Basic version - basic_car (no vision functions): Move, Navigation, RecordMapLocation, GetMapMapping
  • Standard version - no_ptz (no pan-tilt functions): Move, Navigation, RecordMapLocation, GetMapMapping, SeeWhat, GetBbox, TargetTrack, FollowLine
  • Servo pan-tilt version - ptz (supports all functions)

[!NOTE]

The demo cases in the following chapters use the servo pan-tilt version (ptz) vehicle

5.3 Command Format

All CLI commands follow a unified command format:

xxxxxxxxxx
robot_control call-tool <command-name> --parameter1 <value1> --parameter2 <value2> ...
  • robot_control: The main command of the CLI tool
  • call-tool: The subcommand indicating a tool call
  • <command-name>: The specific tool name registered on the MCP server, such as Move, SeeWhat, TTS, etc.
  • --parameter <value>: The key-value pair of parameters passed as needed; different commands have different numbers and types of parameters

Use robot_control list-tools to view the list of all available CLI commands

6. Demo Cases

  • The robot chassis moves forward 0.5 meters
xxxxxxxxxx
robot_control call-tool Move --distance 0.5 --direction forward

image-20260724112930552

  • Get an image of the environment (only for versions with a camera)
xxxxxxxxxx
robot_control call-tool SeeWhat

image-20260724112822435

[!NOTE]

When the SeeWhat tool is called, it automatically saves the image to "$HOME/microros_ws/cache/image.png"

image-20260724113151630

7. Source Code Analysis

Source Code Path:

xxxxxxxxxx
$HOME/microros_ws/src/multi_brains_pre/cli/robot_control

The CLI tool source code registers the various robot control functions as MCP Tools through the register_actions() function in mcp_action.py. Here, the Move (move the chassis by a specified distance) tool is used as an example to explain the source code:

xxxxxxxxxx
@call_tool_app.command(name='Move')
async def Move(
    *,
    direction: Annotated[str, cyclopts.Parameter(help="Movement direction: 'forward', 'backward', 'turn_left', or 'turn_right'")],
    distance: Annotated[float, cyclopts.Parameter(help="Linear movement distance in meters. Only used when direction is 'forward' or 'backward'. Set to 0.0 for rotation.")] = 0.0,
    angle: Annotated[float, cyclopts.Parameter(help="Rotation angle in degrees. Only used when direction is 'turn_left' or 'turn_right'. Set to 0.0 for linear movement.")] = 0.0,
) -> None:
    '''Move the robot chassis by a specified distance or rotate by a specified angle using odometry feedback.'''
    await _call_tool('Move', {'direction': direction, 'distance': distance, 'angle': angle})

Code explanation:

  1. @call_tool_app.command(name='Move'): Uses the cyclopts framework to register the function as a CLI subcommand; name defines the command name, corresponding to the tool name registered on the MCP server
  2. Function parameters: CLI parameters are defined through the Annotated type annotation plus cyclopts.Parameter; help sets the parameter description. direction is a required parameter, while distance and angle are optional parameters with a default value of 0.0
  3. _call_tool: A unified tool call function. Internally, it connects to the MCP server through fastmcp.Client, filters the parameters, sends them to the server for execution, and prints the returned result
Openclaw Robot Mcp Service Integration
Robot-Control Plugin Tools

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