Mobile and ROS robots

MentorPi T1

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

Raspberry Pi
Suggested for secondary
Suggested for university

MentorPi T1 is the tank version of MentorPi: a Raspberry Pi 5 robot car on a tracked chassis that runs ROS2. Closed-loop encoder motors, a lidar and a camera cover SLAM mapping, path planning, vision recognition and autonomous driving, and YOLOv11 detects road signs and traffic lights. The Starter Kit has a monocular camera and the Standard and Advanced kits an Aurora930 Pro 3D depth camera. The Advanced Kit adds an AI voice interaction module for ChatGPT voice control 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 T1 Starter · MentorPi T1 Standard · MentorPi T1 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.

Tracked chassis
A full metal aluminium chassis on tracks, driven by Hall encoder geared motors. The 7.4V LiPo battery runs it for up to 60 minutes.
Lidar navigation
The lidar handles obstacle avoidance, target following, fixed-point and multi-point navigation, path planning and global task navigation.
Aurora930 Pro depth camera
In the Standard and Advanced kits, the depth camera handles depth image data, point clouds, and 3D visual mapping and navigation.
Vision and YOLO
With OpenCV the car tracks colours and targets, follows coloured lines 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. ChatGPT also drives colour tracking, vision tracking and line patrolling with obstacle avoidance.
Control
Drive it from the WonderPi app on iOS or Android, from a PC, or with a wireless controller over Bluetooth.

Where it is used

Applications.

ROS2 teaching on Raspberry Pi 5
SLAM mapping and navigation on a tracked robot
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.

Chassis type: Tank chassis
Size: 27.8 × 19.5 × 18.2 cm (depth camera version)
Weight: 1.88kg (depth camera version)
Motor: Hall encoder DC geared motor
Encoder: AB-phase incremental Hall encoder
Material: Full metal aluminum alloy chassis, anodizing process
ROS controller: RRC Lite controller + Raspberry Pi 5 controller
Camera: Monocular camera (Starter Kit); Aurora930 Pro 3D depth camera (Standard and Advanced Kit)
Depth camera working distance: 15-300 cm
Depth accuracy: ±8mm @1m
Depth resolution / frame rate: 640×400 @12fps (FOV: 74°×51°)
Camera servo: LFD-01 anti-stall servo (Starter Kit)
Voice: WonderEcho Pro AI voice interaction box (Advanced Kit)
Battery: 7.4V 2200mAh 10C LiPo battery with protection board (continuous operating time: up to 60 minutes)
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
Supporting materials: Development tutorials, video tutorials, ROS source code, system image and software
Package weight and size: Around 3.2kg; 39.7 × 24.4 × 22 cm