Wall Following Algorithm for a Mobile Robot Using Extended Kalman Filter

Abstract

This thesis proposes a wall-following algorithm for mobile robots using the Extended Kalman Filter. The robot navigates in a known environment where the baseboard of the wall is used as a natural landmark and indentified by using the Hough transform. The prediction phase of the Kalman Filter is implemented using the odometry model of the robot. The update phase directly uses the parameters of the lines detected by the Hough algorithm to correct the robot's pose. A proportional control is then performed to adjust the speeds on the wheels of the robot so that it follows the wall in a straight line. The results provided by the Matlab simulation environment showed that the wall-following algorithm could converge well to the real world values.