Application of data fusion algorithm based on Kalman filter in mobile robot position measuring system

A data fusion scheme for mobile robots with multiple sensors is proposed in this work. The task is to reduce and eliminate the pose error of robot produced by restriction uncertainty between robot wheels and the ground. Kalman filter (KF) is used to fuse several kinds of data from encoders, gyroscope and ultrasonic sensors. The program of one dimension KF is brief, it can be complicated in each servo cycle. With the proposed data fusion scheme, the path tracking and point positioning was accomplished under the industrial conditions. By data fusion of sensor signals, random error of path tracking was reduced, moreover, final position precision of the mobile robot was improved through ultrasonic sensors.