Hiwonder MentorPi T1 is a smart raspi car robot powered by Raspberry Pi 5 and supports ROS2. Equipped with tank chassis, high-speed closed-loop encoder motors, Lidar, a 3D depth camera, and large-torque servos, it delivers high-performance capabilities. These include SLAM mapping, path planning, vision recognition, and autonomous driving. With YOLOv11 model training, MentorPi T1 can detect road signs and traffic lights. MentorPi open source robot car also deploys a Multimodal Large AI Model to support more advanced embodied AI applications. To help you unlock its full potential, we offer comprehensiveMentorPi T1 tutorialsand videos designed to inspire and support your AI creative projects.
Aurora930 Pro depth camera
The 3D depth camera powers the AI visuals and handles advanced tasks like depth image data processing and 3D visual mapping/navigation.
Raspberry Pi 5 Controller
MentorPi robot is powered by Raspberry Pi 5 controller, allowing you to embark on motion control, machine vision, and OpenCV projects.
Oradar MS200 Lidar
MentorPi features integrated Lidar for intelligent SLAM mapping and navigation. It expertly handles path planning, fixed-point navigation, and dynamic obstacle avoidance.
High Performance Encoder Motor
This motor combines robust power with a high-precision encoder, all housed in a protective end shell for extended durability and life.
Dual-Controller Design for Efficient Collaboration
Function List
Large AI Model Meets SLAM Mapping/Navigation
MentorPi chatgpt robot applies a multimodal large model to understand users' voice commands, enabling multi-point navigation. Once it arrives at the designated location, it uses a vision language model to gain a deep understanding of the surrounding objects and events. This approach greatly enhances the robot's intelligence, adaptability, and overall user experience, making it better suited to meet real-world needs.
Semantic Understanding
MentorPi T1 leverages a large language model to accurately interpret and analyze user voice commands, enabling a deeper understanding of natural language intent.
Environmental Perception
Powered by a vision language model, Hiwonder MentorPi can interpret objects in its surroundings and understand the spatial layout of the environment.
Intelligent Navigation
MentorPi continuously sends environmental data to the vision language model for real-time in-depth analysis. It dynamically adjusts its navigation path based on user voice commands, allowing it to autonomously navigate to designated areas and deliver intelligent, adaptive routing.
Scene Understanding
With the support of a vision language model, MentorPi car can deeply interpret the semantic information of its environment, including surrounding objects and events within its field of view.
AI Large Language Models Embodied
MentorPi T1 robot car is equipped with a high-performance AI voice interaction module. Unlike conventional AI systems that operate on unidirectional command-response mechanisms, MentorPi leverages ChatGPT to enable a cognitive transition from semantic understanding to physical execution, significantly enhancing the fluidity and naturalness of human-machine interaction. Combined with machine vision, Hiwonder MentorPi exhibits advanced capabilities in perception, reasoning, and autonomous action—paving the way for more sophisticated embodied AI applications.
Voice Control
With ChatGPT integration, MentorPi chatgpt robot can comprehend spoken commands and carry out corresponding actions, enabling intuitive and seamless voice-controlled interaction.
Color Tracking
MentorPi utilizes vision language model analysis to detect and lock onto any object within its field of view. With the integration of a PID algorithm, it achieves precise and real-time target tracking.
Autonomous Patrolling
Utilizing semantic understanding from a large language model, MentorPi can accurately detect and track lines of various colors in real time while autonomously navigating obstacles, ensuring smooth and efficient patrolling.
Vision Tracking
With the advanced perception capabilities of a vision AI large language models, MentorPi T1 car can intelligently identify and lock onto target objects even in complex environments, allowing it to perform real-time tracking with adaptability and precision.
Color Recognition and Tracking
Working with OpenCV, MentorPi can track specific color. After you select the color on the app, it emits light of corresponding color and moves with the object of that color.
Target Tracking
Through vision positioning of the target object, the target object can be better targeted and tracked.
QR Code Recognition
MentorPi can recognize the content of custom QR codes and display the decoded information.
Vision Line Tracking
MentorPi raspi robot supports custom color selection, and the robot can identify color lines and track them.
Wireless Controller Control
MentorPi supports wireless controller control and can connect to the robot via Bluetooth to control the robot in real time.
App Control
WonderPi app supports Android and iOS. Switch game modes easily and quickly to experience various AI games.
ROS Robot Operating System
Global Popular Robotic Communication Framework
ROS is an open-source meta operating system for robots. It provides some basic services, such as hardware abstraction, low-level device control, implementation of commonly used functionality, message-passing between processes, and package management. And it also offers the tools and library functions needed to obtain, compile, write, and run code across computers. It aims at providing code reuse support for robotics research and development.
Monocular Camera Parameters
Resolution
30W(640*480)
Light-sensitive chip
GC0308(gcoreinc)
Camera type
HS-256-650(HS)
Aperture
2.0
Focus
1.7mm
Focal field of view angle
170°
Distortion
-83%
Camera interface
USB
Size
30*27*25mm
LFD-01 Servo Parameters
Rotation speed
≤0.11sec/60° 6V
Anti-blocking protection
Power cut protection after 5 seconds of stall
Rotation range
0-180 degrees
Communication method
PWM pulse-width control
Gear type
Plastic shaft
Working voltage
4.8-6V
Maximum torque
≥1.4kg.cm 6V
No-load speed
≤0.11sec/ 60° 6.0V
Size
22.3x12.0x23.2mm
Aurora930 Pro Specifications
Module parameter
Size
76.5 × 20.7 × 21.8 mm
Imaging performance
Depth data format
16-bit Raw
Baseline
40mm
Depth resolution/Frame rate
640×400 @12fps (FOV: 74°×51°)
Interface
USB 2.0 Wafer connector
RGB data format
NV12
Depth accuracy
±8mm @1m
RGB resolution /Frame rate
640×400 @12fps (FOV: 74°×51°)
Working distance
15–300 cm
IR data format
8-bit Raw
Operating temperature
-10℃ to 55℃
IR resolution /Frame rate
640×400 @12fps (FOV: 74°×51°)
Operating humidity
0% to 95% RH (non-condensing)
Firmware capabilities
Firmware upgrade
Supports USB OTA Update
Operating illuminance
3–80,000 Lux
Hot start delay
<300ms
Power supply
5V±10%, 1.5A
System compatibility
OS compatibility
Linux / ARMv8 / ROS / Windows
Power consumption
Average <1.6W
Safety rating
Class 1 Laser safety
Wrapped Rear Tail Shell
It can effectively protect the PCB circuit and magnetic ring at the end of the motor from external influences, effectively improving the safety and service life of the motor.
Permanent Magnet Brushed Motor
The permanent magnet DC motor has fast starting response speed, large starting torque and smooth speed change.
High-precision Magnetic Encoder
The motor is equipped with a high-precision magnetic encoder, has strong horsepower, high precision, and strong anti-interference ability.
Durable Metal Gear
The motor incorporates a full metal gear and metal output shaft, reducing power consumption and extending the motor's service life.
Hall Encoder Geared Motor
The Hall speed measurement code disc is a speed measurement module that utilizes Hall sensor encoders. Equipped with a strong magnetic disc, it generates AB phase output pulse signals, enabling the detection of motor rotation direction and speed.
7.4V 2200mAh 10C LiPo Battery
The LiPo battery features high-quality 18650 cells and a built-in protection board that safeguards against damage from overcharging, overcurrent, overdischarge, and short circuits. It provides a long service life, with over 300 charge cycles.
Chassis type
Tank chassis
Size
27.8*19.5*18.2cm
Weight
1.88kg
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
Aurora930 Pro 3D depth camera
Lidar
Oradar MS200
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
Servo
LFD-01 anti-stall servo (monocular camera version)
Materials
Development tutorials; video tutorials; ROS source code, system image and software
Package size & weight
around 3.2kg; 39.7*24.4*22cm
Product Parameters
Dimensional Diagram
MentorPi T1 Packing List(Monocular Camera Version)
MentorPi T1 Packing List(Depth Camera Version)
Hiwonder MentorPi T1 Raspberry Pi Robot Car – Tank Chassis
Starter Kit with Raspberry Pi 5 4GB
Robot Pi Shop
Pickup currently unavailable
Ground Floor Shop, Sayde Street, Fanar Matn 1202 Fanar Lebanon
