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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

8. Object Follow

Object Follow (No-PTZ)

Function package: microros_v2_kcf_follow_pkg

1. Function Description

microros_v2_kcf_follow_pkg is a following controller based on the target bounding box. It only subscribes to the target box published by the tracking node, and then controls the PTZ and/or body motion.

Therefore, the complete functionality consists of two parts:

  1. The tracker is responsible for obtaining the target bounding box from the image, for example smart_tracker/super_tracker or the KCF tracking node.
  2. tracking_bbox_follow_node computes the PTZ angle, body angular velocity, and body linear velocity from the target box center and target box size.

The default control rate is 10 Hz. When the target box is invalid, the confidence is too low, or it has not been updated for more than target_stale_timeout_sec, the node immediately publishes zero velocity; the source code has no "allow continued motion for 5 frames" lost-target tolerance logic.

2. Control Chain

Camera/visual tracker
    └── /tracking_bbox
          └── tracking_bbox_follow_node (10 Hz)
                ├── PTZ following: target center -> /cmd_ptz_angle
                ├── Body turning: target horizontal error or PTZ deflection -> /cmd_vel.angular.z
                └── Distance following: target box size error -> /cmd_vel.linear.x

PTZ Version

By default enable_ptz_follow:=true:

  • Uses independent X/Y PD control to update the PTZ angle from the pixel error of the target center relative to the image center.
  • After the PTZ horizontal angle deviates from the initial angle by servo1_engage_deg, body PD control is used for angular.z, letting the body gradually follow the PTZ back to center.
  • At the same time, linear.x can be controlled based on the target box size.

No-PTZ Version

A fixed camera cannot adjust its line of sight through the PTZ; the following must be set at startup:

xxxxxxxxxx
enable_ptz_follow:=false publish_initial_ptz_command:=false

In this case, the node uses the horizontal pixel error of the target center to control the body angular.z, and controls linear.x based on the target box size. Setting only publish_initial_ptz_command:=false does not disable the PTZ following logic, so it cannot be the only modification for a No-PTZ configuration.

3. Topics and Messages

TopicDirectionMessage TypeQoSDescription
/tracking_bboxSubscribeAuto-detected by defaultBEST_EFFORT, depth=1Target bounding box input
/cmd_velPublishgeometry_msgs/msg/TwistBEST_EFFORT, depth=1linear.x forward/backward, angular.z left/right turn
/cmd_ptz_anglePublishgeometry_msgs/msg/Vector3depth=10Published in PTZ mode; x is the horizontal angle and y is the pitch angle, in degrees
/JoyStateSubscribestd_msgs/msg/Booldepth=10When true, pauses automatic following and publishes zero velocity

The node is also compatible with:

  • smart_tracker/msg/TrackBox, auto-detected via tracking_bbox_msg_type:=auto;
  • std_msgs/msg/Int32MultiArray: when the length is at least 11, it is parsed as [valid, x1, y1, x2, y2, cx, cy, width, height, image_width, image_height]; when the length is 4 to 10, the first four elements are taken as the bounding box;
  • messages with x1, y1, x2, y2 fields.

The bounding box format is uniformly the top-left corner (x1, y1) and the bottom-right corner (x2, y2). The node automatically sorts the coordinates and checks the width, height, and confidence.

4. Startup Steps

The following commands assume the workspace is ~/microros_car_v2_ws and the ROS 2 environment has been configured.

4.1 Start the Chassis, Agent, Camera, and Model

Terminal 1:

xxxxxxxxxx
ros2 launch microros_v2_bringup car_base.launch.py

image-20260728174751498

4.2 Start the Target Tracker

Run the program smart_tracker/super_tracker, Terminal 2:

xxxxxxxxxx
ros2 launch microros_v2_bringup super_tracker.launch.py display_windows_only_track:=false display_windows:=true

image-20260728180244635

Press c to enter box-selection mode, then use the mouse to draw a box

image-20260728180329711

Then press Enter to start following the coordinate data.

image-20260728180357190

4.4 Start the Follow Controller

Terminal 3:

xxxxxxxxxx
ros2 launch microros_v2_kcf_follow_pkg tracking_bbox_follow.launch.py \
  enable_ptz_follow:=false \
  publish_initial_ptz_command:=false

After a successful startup, slowly move the object to test left/right tracking and forward/backward following.

image-20260728180455252

5. Distance Following Algorithm

The node does not estimate distance from the color radius, but instead uses the geometric size of the bounding box:

xxxxxxxxxx
current_size = sqrt(width * height)
size_error = (target_size - current_size) / target_size

By default auto_set_target_bbox_size:=true. The first valid bounding box received after startup is used as the target distance reference. You can also manually specify target_bbox_size_px, in which case the node no longer waits for the first bounding box to initialize the reference.

The distance control uses the PID form; with the default distance_ki:=0.0, it is effectively PD:

xxxxxxxxxx
linear.x = linear_dir * (distance_kp * size_error
                       + distance_ki * integral
                       + distance_kd * d_error)
  • When the target box is smaller than the reference, size_error > 0, and it moves forward to approach by default;
  • When the target box is larger than the reference, size_error < 0, and it moves backward to retreat by default;
  • When abs(size_error) <= distance_tolerance_ratio, it stops moving forward/backward;
  • linear.x is clamped to [-max_linear_x, max_linear_x], with a default maximum absolute value of 0.12 m/s.

6. Key Parameters

General Parameters

ParameterDefaultDescription
tracking_bbox_topic/tracking_bboxTarget box input topic; the node must be restarted after changing
tracking_bbox_msg_typeautoAuto-detect the message type; you can also fill in the full ROS type name
cmd_vel_topic/cmd_velBody velocity output topic; the node must be restarted after changing
ptz_command_topic/cmd_ptz_anglePTZ angle output topic; the node must be restarted after changing
joy_state_topic/JoyStateJoystick override state topic; the node must be restarted after changing
enable_followtrueMaster follow switch; when disabled, continuously publishes zero velocity
enable_ptz_followtrueEnable PTZ following; must be set to false for No-PTZ
enable_body_turn_followtrueEnable body horizontal turning
enable_distance_followtrueEnable forward/backward distance following
enable_joy_overridetruePause automatic following when the joystick takes over
image_width / image_height640 / 480Used when the input message does not provide the image size
tracking_confidence_threshold0.1Minimum valid confidence
target_stale_timeout_sec1.2Stops the car when the target box has not been updated for longer than this time
follow_rate_hz10.0Control timer rate, minimum 1 Hz

PTZ and Body Turning Parameters

ParameterDefaultDescription
pixel_tolerance15.0 pxPTZ horizontal/pitch pixel deadband
kp_x / kd_x0.6 / 0.15PTZ horizontal PD coefficients
kp_y / kd_y0.6 / 0.15PTZ pitch PD coefficients
max_step_xy5.0 degMaximum PTZ angle step per control cycle
horizontal_min_deg / horizontal_max_deg-90 / 90 degHorizontal angle limits
pitch_min_deg / pitch_max_deg-90 / 20 degPitch angle limits
initial_horizontal_deg0.0 degInitial horizontal angle, also the reference angle for the body to return to center
initial_pitch_deg-45.0 degInitial pitch angle
body_kp / body_kd0.03 / 0.0Body turning PD coefficients in PTZ mode
servo1_engage_deg5.0 degBody turning starts when the PTZ horizontal deflection reaches this value
body_tolerance_deg3.0 degDeadband for stopping the body when it returns to center
max_angular_z0.6 rad/sMaximum absolute body angular velocity
body_ff_gain1.0Feed-forward coefficient in PTZ mode that compensates the PTZ horizontal angle based on body angular velocity
fixed_camera_pixel_tolerance15.0 pxNo-PTZ body turning stop deadband
fixed_camera_engage_px30.0 pxNo-PTZ body turning activation threshold
fixed_camera_body_kp / fixed_camera_body_kd0.6 / 0.15No-PTZ body turning PD coefficients
body_dir / fixed_camera_body_dir-1.0 / -1.0Body turning direction correction; change to 1.0 if necessary
sign_x / sign_y1.0 / -1.0PTZ horizontal/pitch direction correction

Distance Following Parameters

ParameterDefaultDescription
target_bbox_size_px0.0Target reference size; when 0, it is automatically set from the first valid box
auto_set_target_bbox_sizetrueWhether to initialize the reference size from the first valid box
distance_tolerance_ratio0.06Relative size deadband, default 6%
distance_kp / distance_ki / distance_kd0.18 / 0.0 / 0.02Distance PID coefficients
distance_integral_limit0.5Integral limit
max_linear_x0.12 m/sMaximum absolute linear velocity
linear_dir1.0Forward/backward direction correction; change to -1.0 if necessary
AprilTag Machine Code Follow
QR Code Recognition Control Action

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