STEM Educational Mecanum-Wheel Robot – Compatible with Arduino UNO & L293D Motor Driver, Modular Plug Design | Explore Sensors, Algorithms & Robotics Engineering

Equipped with four Mecanum wheels and precision DC motors, this Arduino-based robot enables omnidirectional movement — forward, backward, lateral, diagonal, and rotation-in-place. It demonstrates real vector motion, traction control, and torque distribution. Students can analyze motion equations and practice PID optimization in a physical robotics context. Perfect for engineering education, STEM competitions, and research demonstrations
With a built-in HC-06 Bluetooth module and triple infrared tracking sensors, the robot supports smartphone control and autonomous line following. The Bluetooth interface allows real-time speed, direction, and action programming, while IR sensors track contrast lines with high precision. Students explore PWM logic, sensor data feedback, and serial communication in embedded systems.
The ultrasonic module enables real-time distance measurement (2–400 cm) and automatic obstacle avoidance. It teaches sound-wave propagation, echo delay, and distance triangulation. Students can code logic for autonomous stopping, route planning, and multi-sensor fusion—bridging theoretical math with real-world robotics control.
Fully compatible with Arduino IDE, the kit supports C-based and visual drag-and-drop coding. The L293D driver ensures stable multi-motor control, while I²C/SPI/UART ports enable easy sensor integration. Perfect for teaching circuit logic, control structures, and IoT-based robotics extensions.
Tailored for classrooms, maker labs, and home STEM programs, this kit builds comprehensive knowledge of electronics, mechanics, and logic through assembly and experimentation. Includes full manuals, tutorial videos, and project challenges—empowering hands-on creativity and innovation in robotics.

① Real-Time Self-Balancing Control with Gyroscope and Accelerometer

This advanced self-balancing robot kit teaches the core principles of motion physics and control engineering. Equipped with the MPU6050 gyroscope and accelerometer, the system continuously detects tilt angles and uses real-time PID (Proportional-Integral-Derivative) algorithms to maintain upright balance. Students learn how feedback loops, angle calculations, and sensor fusion work in real autonomous robots. By adjusting PID parameters, users can experiment with dynamic stability, inertia compensation, and center-of-gravity control — skills directly applicable to modern robotics, drones, and AI-controlled mobility systems.