A redundant sensor system, which consists of two incremental encoders and a gyro sensor, has been proposed for the estimation of the posture of mobile robots. A hardware system was built for estimating the heading angle change of the mobile robot fr...
A redundant sensor system, which consists of two incremental encoders and a gyro sensor, has been proposed for the estimation of the posture of mobile robots. A hardware system was built for estimating the heading angle change of the mobile robot from outputs of the gyro sensor. The proposed hardware system of the gyro sensor produced an accurate estimate for the heading angle change of the robot. A sensor data fusion algorithm has been developed to find the optimal estimates of the heading angle change based on the stochastic measurement equations of our readundant sensor system. The maximum likelihood estimation method is applied to combine the noisy measurement data from both encoders and gyro sensor. The proposed fusion algorithm demonstrated a satisfactory performance, showing significantly reduced estimation error compared to the conventional method, in various navigation experiments.