Hiwonder MentorPi M1 Raspberry Pi Robot Car (Standard Kit)

Specifications

• Product Name: Hiwonder MentorPi M1 ROS2 Robot Car (Standard Kit)
• Primary Controller Compatibility: Raspberry Pi 5 (4GB / 8GB recommended)
• Operating Software / ROS Version: ROS2 Humble / Ubuntu Linux
• Drive System: 4-Wheel Independent Drive Mecanum Wheel Chassis (Omnidirectional Movement)
• Drive Motors: Coreless DC Geared Motors with Magnetic Quadrature Encoders
• Primary Distance & SLAM Sensor: TOF Lidar Module (360° Scanning)
• Vision System: 3D Depth Camera (RGB + Depth Sensing)
• Operating Voltage: 7.4V DC 200mAh (Powered via High-Current Rechargeable LiPo Battery Pack)
• Control Interfaces: Wi-Fi, Ethernet, Bluetooth, ROS2 Teleop Node
• Chassis Dimensions: 212mm × 171mm × 147mm
• Weight: 1.200 kg 
• AI & Computer Vision Functions: 2D/3D SLAM Mapping, Autonomous Path Planning, Obstacle Avoidance, Target Tracking, Color Recognition, Tag Following

Unlock New Capabilities

• Past Projects: If you've already experimented with basic 2WD smart cars or built simple line-following robots using microcontrollers, you already understand the fundamentals of motor control and sensor feedback — which means you're perfectly ready to step up to a professional-grade ROS2 environment.
• Feature Upgrade: This MentorPi M1 standard kit unlocks true omnidirectional movement, real-time 2D and 3D SLAM mapping, AI-driven object tracking, and autonomous path planning. These are industry-standard robotics concepts and autonomous navigation builds you simply cannot achieve reliably with basic ultrasonic sensors and standard DC motors.
• Effort Level: Advanced

Minimum hardware to get started:

• Raspberry Pi 5 (4GB or 8GB recommended): to serve as the main computing brain required to run ROS2 Humble nodes, process SLAM algorithms, and handle 3D vision data.
• Laptop or PC running Ubuntu Linux: to remotely interface with the robot, run the ROS2 host environment, and visualize RViz mapping telemetry wirelessly.
• MicroSD Card (32GB+ Class 10): to flash the Ubuntu operating system and ROS2 workspace required for the Raspberry Pi.

Included in the Box:

• 1× Aluminum Alloy Mecanum Chassis Kit
• 4× Coreless DC Geared Motors with Magnetic Encoders
• 4× Mecanum Wheels
• 1× MentorPi ROS2 Expansion Board
• 1× 360° TOF Lidar Sensor
• 1× 3D Depth Camera (RGB-D)
• 1× 7.4V High-Capacity LiPo Battery & Charger
• Assembly Hardware, Cables, and Screws

Frequently Asked Questions

• Is the MentorPi M1 compatible with older Raspberry Pi models?
  While it technically connects, a Raspberry Pi 5 (4GB+ recommended) is strongly advised due to the heavy processing requirements of 3D SLAM mapping and AI vision nodes.
• Can I use this robot with ROS1 instead of ROS2?
  The provided software images, launch nodes, and tutorials are specifically built and optimized for ROS2 Humble, making ROS1 integration a highly complex manual task.
• Does the MentorPi standard kit include the WonderEcho Pro AI Voice Box?
  No, this standard kit configuration does not include the WonderEcho Pro module, but it can be purchased and integrated separately as an upgrade.
• Is the robot compatible with Python for custom programming?
  Yes, the ROS2 environment fully supports both Python (rclpy) and C++ (rclcpp) for writing custom autonomous navigation and vision processing scripts.
• How is the Raspberry Pi powered in this kit?
  The Raspberry Pi is powered directly from the MentorPi expansion board, which safely steps down the 7.4V LiPo battery voltage to a stable 5V, high-current output.
• Can I power the robot via a USB wall adapter during development?
  It is best to use the fully charged LiPo battery, as the drive motors, Lidar, and 3D camera require significant peak current that a standard USB adapter cannot provide without browning out.
• How long does the 7.4V LiPo battery last on a single charge?
  Depending on the complexity of your AI algorithms and motor usage, you can expect approximately 45 to 90 minutes of continuous autonomous operation.
• Where should the 3D Depth Camera be plugged in?
  The 3D camera must be connected to one of the blue USB 3.0 ports on the Raspberry Pi 5 to ensure sufficient bandwidth for depth data processing.
• How does the TOF Lidar connect to the system?
  The TOF Lidar connects directly to a dedicated pre-crimped JST sensor port on the MentorPi expansion board, removing the need to wire it directly to the Pi's GPIO pins.
• Do I need to solder any wires during assembly?
  No, the entire kit is designed to be plug-and-play, using modular JST connectors and standard USB/ribbon cables for a clean and safe build.
• Where can I find the ROS2 workspace for the MentorPi?
  The easiest setup method is to flash the pre-configured Ubuntu/ROS2 image provided by Hiwonder, which contains the fully compiled workspace ready to run out of the box.
• Can I control the robot using my smartphone?
  Yes, Hiwonder provides a dedicated mobile application that interfaces directly with the robot's network for teleoperation, parameter tuning, and FPV viewing.
• What SLAM mapping algorithms are supported out of the box?
  The provided software stack supports standard ROS2 mapping algorithms, including Cartographer and RTAB-Map, allowing you to generate both 2D floor plans and 3D point cloud environments.
• Why is the 3D camera node crashing when I launch the ROS2 file?
  This usually happens if the camera is mistakenly plugged into a black USB 2.0 port instead of a blue USB 3.0 port, causing a severe bandwidth bottleneck.
• Why does the robot drift instead of moving in a straight line?
  Drifting is almost always caused by loose mecanum wheel encoder wires; carefully verify that all four motor JST connectors are firmly seated on the expansion board.
• Why is my mapping data jumping or failing to align in RViz?
  Ensure the TOF Lidar has an unobstructed 360-degree view and that you are not mapping in a completely featureless hallway with highly reflective surfaces like glass.
  
• My Raspberry Pi is showing a low voltage warning, what should I do?
  Stop the robot and recharge the main 7.4V LiPo battery immediately, as the expansion board will pass this warning to the Pi when the battery drops below its optimal safe voltage.