Overview
MicroROS-Pi5 is a ROS2 Robot Car developed for Raspberry Pi 5, using Raspberry Pi OS + ROS2 Humble and Python 3. It integrates a MicroROS robot expansion/control board with an ESP32 co-processor, MS200 TOF laser LiDAR, a 2MP camera on a 2DOF PTZ pan/tilt, 4PCS 310 encoder motors, an anodized aluminum alloy frame/body, and a 7.4V 2000mAh rechargeable battery. OpenCV image processing and MediaPipe machine learning algorithms are used to support robot motion control, AI visual interaction, SLAM mapping/navigation, RViz simulation, and multi-machine synchronous control.
Key Features
- Raspberry Pi 5 power solution: provides 5.1V/5A power supply for Raspberry Pi 5 (supports PD), designed to ensure sufficient USB interface current and stable operation.
- Dual-controller architecture: Raspberry Pi 5 as the ROS controller (upper-level) for visual processing and mapping; ESP32 as the lower-level co-processor for motor drive, servo angle control, IMU acquisition, and LiDAR/camera drive.
- MS200 TOF LiDAR functions: SLAM mapping (gmapping and cartographer), path planning, single-point and multi-point navigation with obstacle avoidance, iOS/Android app mapping navigation, multi-machine navigation, and LiDAR-based behaviors (avoid, tracking, guard, patrol).
- AI visual recognition & interaction: OpenCV + MediaPipe; face/body/gesture/picture-code recognition; QR code recognition; AR vision (12 AR visual effects with chessboard paper); color/face/KCF object tracking; line tracking; gesture-controlled movements and autopilot color following.
- 2DOF camera PTZ: USB high frame rate HD camera with metal servos; supports horizontal 180° and vertical 180° electric rotation for motion tracking and AI visual development.
- Chassis/body design: aluminum alloy body, enclosed cabin design, geometric hollow heat dissipation holes, reserved holes for wiring, EVA anti-collision cotton, and PWM adjustable-speed active cooling (Cool cooler Pi50).
- Multiple control methods: mobile app control (forward/backward/turn left/turn right with real-time camera view), handle control for multi-robot synchronous control, and keyboard control for multi-robot synchronous control.
- RViz simulation support for development feedback, debugging, testing, and algorithm verification in a virtual environment.
Specifications
| Product | MicroROS-Pi5 ROS2 Robot Car for Raspberry Pi 5 |
| OS / ROS | Raspberry Pi OS + ROS2 Humble |
| Programming Language | Python 3 |
| Main Controller | Raspberry Pi 5 (optional configuration) |
| Co-Processor | ESP32 (MicroROS robot expansion/control board; ESP32S3 dual-core development board is referenced in product material) |
| LiDAR | MS200 TOF laser LiDAR (ORBBEC MS200 referenced) |
| LiDAR Measurement Radius | Up to 12m |
| LiDAR Blind Zone | 3cm |
| LiDAR Ranging Error | ±2mm within 2 meters |
| LiDAR Sampling Frequency | 4500 times/s |
| LiDAR Scanning Frequency | 7HZ~15HZ |
| LiDAR Communication Rate | 230400bps |
| Camera | 2MP; USB high frame rate HD camera |
| Camera Pan/Tilt | 2DOF PTZ; horizontal 180° electric rotation; vertical 180° electric rotation |
| Motors | 4PCS 310 reduction motor with encoder (metal encoder reduction motor referenced) |
| Motor Reduction Ratio | 1:20 |
| IMU | 6-axis IMU sensor (3-axis accelerometer + 3-axis gyroscope) |
| Battery Pack | 7.4V 2000mAh lithium battery pack |
| Power for Raspberry Pi 5 | 5.1V/5A (supports PD) |
| Frame/Body | Anodized aluminum alloy; enclosed cabin; EVA anti-collision cotton |
| Cooling | Cool active heat sink; PWM adjustable speed fan; aluminum alloy heat sink (Cool cooler Pi50 referenced) |
MicroROS Control Board Interfaces (from product material)
| Power / Charging | Battery interface; battery charging interface; Type-C power supply interface; 5V OUT; switch |
| Communication | WiFi; Bluetooth; Type-C serial port; antenna interface |
| Peripherals | LiDAR interface; PWM servo interface; supports 4-channel encoder motors; supports 2-channel PWM servos; buzzer |
| Controls / Indicators | Reset button; BOOT button; custom buttons; power indicator light and MCU indicator light |
| Sensors / Expansion | 6 axis IMU chip; custom GPIO * 2 |
Raspberry Pi 5 Board Reference (from product material)
| Item | Raspberry Pi 5 | Raspberry Pi 4B |
| CPU | Quad-core Cortex-A76 Broadcom BCM2712 (2.4GHz Main frequency) | Quad-core Cortex-A72 Broadcom BCM2711 (1.5GHz Main frequency) |
| GPU | 800 MHz VideoCore VII | 600 MHz VideoCore VI |
| Memory | LPDDR4X-4267 SDRAM | LPDDR4-3200 SDRAM |
| Power Input | 5.1V/5A (Support PD) | 5V/3A (Not support PD) |
| Fan Interface | PWM control and tacho Feedback (4 pins JST) | None |
Configuration Options
- Without Raspberry Pi 5 board: with 64GB TF card (system file written). Suitable for users who already have a Raspberry Pi 5.
- With Raspberry Pi 5 board: Raspberry Pi 5 memory options shown as 2/4/8/16GB optional, with 64GB TF card (system file written).
Applications
- ROS2 learning and robotics education
- SLAM mapping, navigation, and path planning development
- Computer vision projects with OpenCV and MediaPipe
- Multi-robot synchronous control and RViz-based simulation workflows
Manuals
For configuration selection, pre-sales questions, and technical support, contact https://rcdrone.top/ or email support@rcdrone.top.
Details

Build ROS2 projects on Raspberry Pi 5 with a compact robot car designed for vision, mapping, and navigation.

A complete development platform that combines ROS2 Humble, Python, and AI vision workflows for real robot behavior.

Core capabilities include onboard computing, LiDAR perception for obstacle-aware navigation, and AI visual recognition.

Get productive faster with structured lessons, practical demos, and technical support for setup and troubleshooting.

Designed around Raspberry Pi 5 power needs to keep USB current stable during camera and sensor workloads.

Choose the kit that fits your lab—reuse an existing Pi 5 or select a ready-to-run bundle.

A 2DOF pan/tilt camera mount enables tracking experiments and flexible viewpoints for OpenCV and MediaPipe tasks.

Interactive demos cover object tracking, color-follow autopilot, and gesture-based motion control.

Use TOF LiDAR for SLAM mapping, path planning, obstacle avoidance, and coordinated multi-robot navigation.

Control options range from phone-based driving with live video to synchronized multi-robot control by handle or keyboard.

Develop on ROS2 Humble and validate behaviors in RViz before moving from simulation to real-world runs.

A dual-controller design offloads real-time motor and sensor tasks to ESP32 while Raspberry Pi 5 handles ROS and vision.

An exploded layout makes it easy to identify key modules for maintenance, upgrades, and wiring.

Mechanical details focus on durability, airflow, wiring access, and sensor-ready integration for ongoing expansion.

Core components are organized for quick access—LiDAR, pan/tilt camera, and the MicroROS expansion/control board.

A step-by-step curriculum covers setup, robot control, perception, mapping, and common ROS2 workflows.

Deeper lessons include perception pipelines, navigation stacks, and microcontroller-side development tasks.

Open-source project structure helps you locate demos quickly and adapt code into your own ROS2 packages.

MicroROS-Pi5 ROS2 robot resources include organized training materials with English subtitles, technical support, and downloadable 3D model files.

MicroROS Robot-Pi5 dimensions and a quick spec overview help you plan chassis space and ROS2 (Humble) setup around the Raspberry Pi 5 controller.

The MS200 LiDAR and 2DOF camera PTZ module list key setup specs like 360° scan angle, 0.03–12 m range, and operating voltages.

The MicroROS-Pi5 ROS2 robot car kit includes an assembled chassis and wheels, motor set, MS200 LiDAR, 200° camera PTZ, control board, covers, controller, and key accessories like cables and a charger.
