Mobile and ROS robots

MentorPi M1

A Raspberry Pi 5 mecanum wheel robot car for ROS2, with lidar SLAM, AI vision and YOLO detection.

Raspberry Pi
Suggested for secondary
Suggested for university

MentorPi M1 is the mecanum wheel version of MentorPi, a robot car built on the Raspberry Pi 5 and ROS2. Closed-loop encoder motors, a lidar and a camera cover SLAM mapping, path planning and autonomous driving, and YOLOv11 detects road signs and traffic lights. The Starter Kit has a monocular camera and the Standard and Advanced kits a 3D depth camera. The Advanced Kit adds an AI voice interaction module that links the car to ChatGPT and vision language models. Hiwonder provides tutorials and videos.

Zeta42 is an authorised Hiwonder partner in the Middle East.

Configurations

Choose how it ships.

Model: MentorPi M1 Starter · MentorPi M1 Standard · MentorPi M1 Advanced
Controller: Without Raspberry Pi 5 · With Raspberry Pi 5 2GB · With Raspberry Pi 5 4GB · With Raspberry Pi 5 8GB · With Raspberry Pi 5 16GB

What it does

Built for.

Lidar navigation
The lidar handles obstacle avoidance, target following, fixed-point and multi-point navigation, path planning and global task navigation.
3D depth camera
In the Standard and Advanced kits, the depth camera adds 3D visual mapping and navigation, giving the car a fuller picture of its surroundings.
Vision and YOLO
With OpenCV the car tracks colours and targets, follows lines of any chosen colour and decodes QR codes. YOLOv11 detects road signs and traffic lights for model autonomous driving.
Voice and large AI models
In the Advanced Kit, a language model turns voice commands into multi-point navigation, and a vision language model describes the objects and events it finds on arrival.
Mecanum chassis
A full metal aluminium chassis on mecanum wheels, driven by metal-gear encoder motors, moves forwards, sideways, diagonally and on the spot.
Control
Drive it from the WonderPi app on iOS or Android, from PC software, or with a wireless controller over Bluetooth.

Where it is used

Applications.

ROS2 teaching on Raspberry Pi 5
SLAM mapping and navigation projects
Model autonomous driving with road sign and traffic light detection
Embodied AI with voice commands (Advanced Kit)

Videos

See it run.

Specifications

The full sheet.

Size: 212 × 171 × 147 mm (depth camera version)
Weight: 1.2kg (depth camera version)
Chassis type: Mecanum wheel chassis
Motor: 310 metal gear geared motor
Encoder: AB-phase high-accuracy quadrature encoder
Material: Full metal aluminum alloy chassis, anodizing process
ROS controller: RRC Lite controller + Raspberry Pi 5 controller
Control method: App, wireless handle and PC control
Depth camera: Angstrong binocular 3D depth camera (Standard and Advanced Kit)
Depth camera range: 0.2-4m
Battery: 7.4V 2200mAh 10C LiPo battery
OS: Raspberry Pi OS + Ubuntu 22.04 LTS + ROS2 Humble (Docker)
Software: iOS / Android app
Communication method: WiFi / Ethernet
Programming language: Python / C / C++ / JavaScript
Storage: 64GB TF card
Package size: 41 × 22 × 18 cm (depth camera version)
Package weight: About 2.1kg (depth camera version)