A developer has built a self-balancing robot featuring a custom motor control system powered by an ESP32 microcontroller. The system integrates an H-Bridge circuit with MOSFETs for efficient motor operation, allowing precise bidirectional movement and smooth speed adjustments through Pulse Width Modulation (PWM).
To maintain balance, the robot utilizes an Inertial Measurement Unit (IMU) that combines gyroscope and accelerometer data. A Kalman filter processes these signals, minimizing noise and drift to provide accurate tilt estimation. The ESP32 continuously calculates real-time adjustments, ensuring stable operation.
A custom PCB was designed using CAD software to integrate the motor driver, IMU, and microcontroller. The chassis was 3D-printed for durability while keeping the overall structure lightweight. A boost converter supplies a stable 5V power source to maintain consistent performance.
Testing involved real-time data visualization to validate the Kalman filter’s accuracy. The system responded to tilt changes instantly, adjusting motor speeds dynamically to counteract imbalance. The ESP32’s high processing speed allowed seamless execution of sensor fusion algorithms without delays.
This project highlights the potential of smart motor control, sensor fusion, and algorithm-driven balance correction. With refinements, the system could serve as a foundation for advanced robotics applications, from autonomous self-balancing platforms to robotic assistance devices.
