Sensor fusion to Estimate the Orientation of a Scale Autonomous Vehicle using the Kalman Filter

Abstract

The fusion of different sensors (accelerometer, gyroscope and magnetometer) has been carried out using a Kalman filter in order to obtain an accurate estimation of the orientation of a scale autonomous vehicle. This was used for the correct navigation of the vehicle which participated in the Robocar race competition. Calibration methods have been implemented (for the accelerometer and gyroscope) with a practical approach, so that it can be implemented before the start of the race in real time. The Kalman filter was simulated to determine the influence of the variation of the parameters that intervene in the Kalman filter equations. The response of the instrumentation to the disturbances was improved, which leads to an adequate estimation of the orientation.