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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

Package: microros_v2_kcf_follow_pkg

1. Feature Description

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

Therefore, the complete functionality consists of two parts:

  1. A tracker obtains the target bounding box from the image, e.g. smart_tracker/super_tracker or the KCF tracking node.
  2. tracking_bbox_follow_node computes the pan-tilt angle, the body angular velocity, and the body linear velocity from the target box center and the target box size.

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

2. Control Chain

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

PTZ Version

enable_ptz_follow:=true by default:

  • Based on the pixel error of the target center relative to the image center, independent X/Y PD control updates the pan-tilt angles.
  • Once the pan-tilt horizontal angle deviates from the initial angle by servo1_engage_deg, the body PD control drives angular.z, letting the body gradually follow the pan-tilt back to center.
  • linear.x can be controlled simultaneously based on the target box size.

No-PTZ Version

A fixed camera cannot adjust its line of sight through the pan-tilt, so at startup you must set:

xxxxxxxxxx
enable_ptz_follow:=false publish_initial_ptz_command:=false

In this mode the node uses the target center's horizontal pixel error 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 follow logic, so it cannot be the only change for a No-PTZ configuration.

3. Topics and Messages

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

The node is also compatible with:

  • smart_tracker/msg/TrackBox, auto-discovered 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 (x1, y1) and bottom-right (x2, y2). The node auto-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 is already configured.

4.1 Start the Chassis, Agent, Camera, and Model

Terminal 1:

xxxxxxxxxx
ros2 launch microros_v2_bringup car_base.launch.py

image-20260728161615714

4.2 Start the Target Tracker

Run smart_tracker/super_tracker, Terminal 2:

xxxxxxxxxx
ros2 launch microros_v2_bringup super_tracker.launch.py

image-20260728180244635

Press c to enter the box-selection mode, then select with the mouse:

image-20260728180329711

Then press Enter to start following the coordinate data:

image-20260728180357190

4.3 Start the Follow Controller

Terminal 3:

xxxxxxxxxx
ros2 launch microros_v2_kcf_follow_pkg tracking_bbox_follow.launch.py 

After a successful startup, slowly move the object for left/right tracking and forward/back following:

image-20260728180455252

5. Distance-follow Algorithm

The node does not use the color radius to estimate distance; instead it uses the geometric size of the bounding box:

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

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

Distance control uses the PID form, with distance_ki:=0.0 by default, so it is actually 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 baseline, size_error > 0, the default is to move forward and approach;
  • When the target box is larger than the baseline, size_error < 0, the default is to move backward and move away;
  • When abs(size_error) <= distance_tolerance_ratio, forward/back movement stops;
  • linear.x is limited to [-max_linear_x, max_linear_x], with the default maximum absolute value being 0.12 m/s.

6. Key Parameters

Common Parameters

ParameterDefault ValueDescription
tracking_bbox_topic/tracking_bboxTarget box input topic; changing it requires a node restart
tracking_bbox_msg_typeautoAuto-discovers the message type; a full ROS type name can also be filled in
cmd_vel_topic/cmd_velBody velocity output topic; changing it requires a node restart
ptz_command_topic/cmd_ptz_anglePTZ angle output topic; changing it requires a node restart
joy_state_topic/JoyStateGamepad takeover state topic; changing it requires a node restart
enable_followtrueMaster follow switch; when off, zero velocity is published continuously
enable_ptz_followtrueEnable pan-tilt following; No-PTZ must be set to false
enable_body_turn_followtrueEnable body horizontal turning
enable_distance_followtrueEnable forward/back distance following
enable_joy_overridetruePause auto-follow when the gamepad 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_sec1.2Stop when the target box has not been updated for longer than this time
follow_rate_hz10.0Control timer rate, minimum 1 Hz

Pan-Tilt and Body Turning Parameters

ParameterDefault ValueDescription
pixel_tolerance15.0 pxPTZ horizontal/tilt pixel deadband
kp_x / kd_x0.6 / 0.15PTZ horizontal PD coefficients
kp_y / kd_y0.6 / 0.15PTZ tilt PD coefficients
max_step_xy5.0 degMaximum pan-tilt angle step per control cycle
horizontal_min_deg / horizontal_max_deg-90 / 90 degHorizontal angle limits
pitch_min_deg / pitch_max_deg-90 / 20 degTilt angle limits
initial_horizontal_deg0.0 degInitial horizontal angle, also the body homing reference angle
initial_pitch_deg-45.0 degInitial tilt angle
body_kp / body_kd0.03 / 0.0PTZ-mode body turning PD coefficients
servo1_engage_deg5.0 degBody turning starts when the pan-tilt horizontal deviation reaches this value
body_tolerance_deg3.0 degBody homing stop deadband
max_angular_z0.6 rad/sMaximum absolute body angular velocity
body_ff_gain1.0In PTZ mode, the feedforward coefficient compensating the pan-tilt horizontal angle from the body angular velocity
fixed_camera_pixel_tolerance15.0 pxNo-PTZ body turning stop deadband
fixed_camera_engage_px30.0 pxNo-PTZ body turning start 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/tilt direction correction

Distance-follow Parameters

ParameterDefault ValueDescription
target_bbox_size_px0.0Target baseline size; when 0, set automatically from the first valid box
auto_set_target_bbox_sizetrueWhether to initialize the baseline size from the first valid box
distance_tolerance_ratio0.06Relative size deadband, 6% by default
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/back direction correction; change to -1.0 if necessary
AprilTag Machine Code Follow
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