Positioning System for 4-Wheel Mobile Robot: Encoder, Gyro and Accelerometer Data Fusion with Error Model Method

Abstract

In this sensor fusion approach, combination of filtering encoder, gyro and accel-erometerʼs signals was used to improve and correct the measurement of 4-wheel mobile robot s ̓ own position. The error model method was proposed for fusing encoder information with relative position measurement by gyro sensor and accelerometerʼs information to obtain more reliable position estimation. From this, we computed high-accuracy position estimation and had reduced the systematic and non-systematic errors during traveling and had succeeded in estimating the bias drift of gyro and accelerometer. The basic tool here is a Kalman filter supported by change detection from sensor diagnosis. Results and experience of real-time implementations are presented.