Yahboom MicroROS Self-balancing Robot Car 4KG Load (Standard/AI Vision) ROS2 Humble TOF LiDAR SLAM
Yahboom MicroROS Self-balancing Robot Car 4KG Load (Standard/AI Vision) ROS2 Humble TOF LiDAR SLAM
Yahboom
āĻĒāĻŋāĻāĻāĻĒā§āĻ° āĻāĻĒāĻ˛āĻā§āĻ¯āĻ¤āĻž āĻ˛ā§āĻĄ āĻāĻ°āĻž āĻ¯āĻžāĻ¯āĻŧāĻ¨āĻŋ
Overview
Yahboom MicroROS Self-balancing Robot Car is a two-wheel self-balancing robot car platform designed for ROS2 (Humble) learning and development. It integrates STM32 + ESP32 dual processors, a metal chassis, 520 encoder DC reduction motors, a 6-axis IMU attitude sensor, ultrasonic module, TOF laser LiDAR, and an OLED display. Using MicroROS wireless communication, sensor data (such as LiDAR, odometer, 6-axis sensor, and optional camera) can be transmitted to a PC virtual machine system to complete complex computing tasks and generate decisions for mapping and navigation.
Key Features
- MicroROS wireless communication + virtual machine master control for real-time sensor data transmission and computation on the PC virtual machine
- ROS2 Humble support, with RViz simulation for visualizing system status and SLAM processes
- SLAM mapping & navigation support (gmapping and cartographer algorithms)
- LiDAR functions: wall following, guard (faces nearest target), follow (tracks nearest target), patrol (scans route and stops when encountering obstacles), obstacle avoidance
- Ultrasonic obstacle avoidance/following modes (switchable)
- OLED data display (supports displaying the current mode and voltage of the robot car)
- 4KG load balance capability; 3-layer structure design with an upper platform for carrying items/DIY expansion
- Climbing: supports slopes of about 30°
- Multi-machine synchronous navigation/control (multi-robot navigation on the same map; multi-machine handle control and keyboard control)
- App control: mapping navigation app (iOS/Android) and Bluetooth remote control app (Android only)
For product selection, setup support, and after-sales service, contact https://rcdrone.top/ or email support@rcdrone.top.
Standard vs AI Vision Version
- Standard Version: AI visual interaction functions are not supported.
- AI Vision Version: adds a ROS-WiFi camera module and supports AI vision recognition/interaction. The AI vision version supports viewing video in the mapping navigation app.
AI Vision Functions (AI Vision Version Only)
- QR Code Motion Control (recognize QR code content and execute forward/backward instructions)
- Palm Following
- Gesture Control of Car Movement
- Face Tracking
- Human Posture Tracking
- OpenCV image processing
- MediaPipe machine learning
Specifications
| Model | MicroROS self-balancing robot car (Standard Version / AI Vision Version) |
| Main processor | STM32 + ESP32 dual processors |
| Processor (detailed) | STM32F103RCT6; ESP32-S3-WROOM-1U-N4R2 |
| Host computer / ROS master control | PC virtual machine |
| Wireless mode | WiFi-UDP mode (connects to WiFi-UDP proxy of the virtual machine/computer); Professional mode (STA) suitable for multi-robot control; devices should be within the same network segment |
| LiDAR | TOF LiDAR as standard; TOF laser LiDAR (SLAM) |
| Standard sensors | OLED; Ultrasonic; TOF laser LiDAR (SLAM) |
| IMU | 6-axis IMU attitude sensor |
| Motor | 520 encoder DC reduction motor |
| Encoder | AB phase speed encoder |
| Control algorithm | PID / LQR (supports PID and LQR control) |
| Battery | 2200mAh battery pack |
| Load | 4KG load balance |
| Climbing | About 30° slope |
| Remote control | BT remote control APP; mapping navigation APP; keyboard control; handle control (optional) |
| Mobile apps | Map navigation APP supports iOS/Android; Bluetooth remote control APP only supports Android |
| Camera (vision version) | ROS-WiFi camera module |
| RViz | RViz simulation support |
| Onboard display | OLED data display (mode and voltage) |
| Protection / warning | With battery protection box; low voltage warning function |
| OS / platform note | Not support mac system |
| BT app parameter adjustment | Not support |
Applications
- ROS2 Humble learning and classroom teaching
- SLAM mapping and navigation experiments (gmapping/cartographer)
- Multi-robot coordination demos (multi-machine synchronous navigation/control)
- AI vision interaction projects (AI Vision Version with ROS-WiFi camera module)
Tutorial
Tutorial link: http://www.yahboom.net/study/SBR-microROS
Details
MicroROS wireless communication streams LiDAR/IMU/odometry data to a ROS2 Humble PC (virtual machine) for mapping and navigation.
Choose the Standard kit for core MicroROS + SLAM learning, or the AI Vision version to add the ROS-WiFi camera and vision interaction features.
A WiâFi UDP bridge connects the robot to the ROS2 virtual-machine master, helping keep onboard compute lightweight.
Built-in LiDAR behaviors include wall following, guard/follow modes, patrol scanning, and obstacle avoidance for indoor demos.
ROS2 SLAM workflows support gmapping and cartographer, plus path planning with obstacle avoidance and app-based mapping navigation.
The AI Vision kit adds camera-based interactions such as QR code commands, gestures, palm following, and posture tracking.
Run multiple robots on the same map and coordinate movement using keyboard control or optional gamepad handles.
A 3-layer metal structure supports payloads up to 4 kg, with ultrasonic modes and an OLED readout for status and voltage.
STM32 handles real-time motor control while ESP32 manages MicroROS wireless communication to the ROS2 master.
Use the mapping/navigation app for SLAM workflows, or switch to Bluetooth remote control for quick driving tests.
Learning materials focus on PID speed/position control, with example code and app-based tuning for faster bring-up.
Yahboom includes a study link plus organized folders of documents and English-subtitled tutorial videos to help you get started.
The MicroROS self-balancing robot uses a layered chassis with TOF laser lidar, ultrasonic sensing, an OLED screen, and separate control/communication boards, with an optional ROS WiFi camera module.
The TOF laser lidar module provides 360° scanning with up to 12 m ranging and a 5 cm blind area for navigation and mapping tasks.
The MicroROS self-balancing robot supports an optional ROSâWiFi camera module with 5V power and serial port connection for image capture and video streaming.
The Yahboom MicroROS self-balancing robot chassis uses a 12V geared motor (1:30) with an AB phase incremental Hall encoder (3.3â5V) for feedback control.
The Yahboom MicroROS self-balancing robot uses an ESP32 control board with clearly labeled connectors for motors and add-on modules like OLED, microSD, camera, and ultrasonic sensors.
The Yahboom ESP32 communication board includes labeled connectors for antenna, OLED, UART/serial, and LiDAR, plus BOOT and RESET buttons for setup.
Yahboomâs microROS self-balancing robot includes a detailed dimension layout (194 mm wide, 197 mm tall) to help plan mounting and workspace fit.
The MicroROS self-balancing robot kit includes the car body, Mini Plus laser lidar, ESP32 and STM32 boards, an OLED screen, a 12.6V battery pack, and basic wiring accessories.
Related Collections
