Odometry Correction Using Visual Slip Angle Estimation for Planetary Exploration Rovers

This paper introduces a novel method for slip angle estimation based on visually observing the traces produced by the wheels of a robot on soft, deformable terrain. The proposed algorithm uses a robust Hough transform enhanced by fuzzy reasoning to estimate the angle of inclination of the wheel trace with respect to the vehicle reference frame. Any deviation of the wheel track from the planned path of the robot suggests occurrence of sideslip that can be detected and, more interestingly, measured. In turn, the knowledge of the slip angle allows encoder readings affected by wheel slip to be adjusted and the accuracy of the position estimation system to be improved, based on an integrated longitudinal and lateral wheel–terrain slip model. The description of the visual algorithm and the odometry correction method is presented, and a comprehensive set of experimental results is included to validate this approach.