Abstract: A Two wheel balancing robot are based on inverted pendulum configurations which rely on dynamic balancing systems for balancing and maneuvering. The controller board is equipped with PWM channels and motion sensors such as accelerometers. The processes developed are involved in balancing a two-wheeled autonomous robot based on the inverted pendulum model. The robot utilises a Proportional-Integral-Derivative (PID) controlled differential steering method for trajectory control. The balancing robot platform proved to be an excellent test bed for sensor fusion using the Kalman filter as the methodology. Kalman filter is a set of mathematical equations that provides an efficient computational solution of least squared method. An indirect Kalman filter configuration combining free scale board accelerometers is implemented to obtain an accurate estimate of the derivative and tilt angle. An accelerometer measures acceleration of components that is mounted on it. In sensor world, accelerometer is very important because they can sense a wide range of motion. Accelerometer also detects the angle with respect to gravity. To run the left and right motors, two separate H-bridge are used. An H-bridge is an electronic circuit that enables the voltage applied across in either direction. The aim of the Accelerometer and PID readings is to control the direction of rotation of the DC motors.
Keywords: Accelerometer, Kalman filter, Inverted pendulum, PID Controller, H-bridge, Freedom freescale.