Mecanum Wheel Robot Platform with ROS1 Control & AI Vision Navigation | Dual Controller with ESP32 & Arduino | LiDAR SLAM Mapping & 360° Omni-Directional Drive | Python & C++ Programming for STEM Education & Autonomous Driving Research

This advanced educational robot platform combines ROS 1, AI vision, and a Mecanum-wheel omni-drive system to create a complete solution for teaching robotics, navigation, and artificial intelligence. Designed for universities and research institutions, it allows students to explore every layer of robotic intelligence —from sensor perception to motion control and autonomous decision making.

The robot integrates dual microcontrollers (Arduino and ESP32) to separate motion control from network communication. Arduino handles PWM motor signals, while ESP32 manages Wi-Fi telemetry and ROS topic publishing. This distributed design mirrors real industrial robots where timing and latency are critical for stability.

Equipped with a precision Lidar sensor, IMU module, and camera for computer vision, the platform supports SLAM mapping, path planning, and obstacle avoidance through ROS 1 navigation stacks. Students visualize real-time sensor data in RViz and test algorithms within Gazebo before executing them on the physical robot. This workflow reduces risk and enhances learning efficiency.

The Mecanum drive system enables true 360-degree mobility — forward, backward, sideways, diagonal, and rotation in place. This kinematic freedom simplifies research on motion planning, vector control, and PID stability. Combined with LiDAR mapping and visual feedback, students can create fully autonomous navigation experiments in indoor environments.

Python and C++ programming examples cover topics like sensor fusion, path optimization, and ROS communication between nodes. Each module is documented with launch files and parameter sets so that students can focus on algorithm development rather than hardware wiring. Teachers use this platform to run STEM courses on autonomous systems, AI robotics, and IoT applications.

Because it is open source and modular, additional sensors or mechanical arms can be added for research projects. The robot’s metal chassis ensures durability and accuracy under continuous use. By experimenting with ROS 1 topics, students learn how autonomous robots “think,” sense their environment, and adapt their path in real time — transforming theory into practice.