Non-linear observer for slip estimation of tracked vehicles

Accurate estimation of slip is essential in developing autonomous navigation strategies for mobile vehicles operating in unstructured terrain. This paper presents an accurate and robust technique for the estimation of slip parameters of a tracked vehicle. The technique uses a sliding mode observer (SMO) with sprocket wheel angular velocities and vehicle trajectory as inputs and estimates slip parameters by minimizing the errors between the predicted trajectory and the measured trajectory. The error dynamics is proven to converge after a finite time from any arbitrary point in error space and remains in the neighbourhood of the sliding motion. Slip estimation schemes using an extended Kalman filter (EKF) and direct mathematical inversion of the kinematic equations are also presented for comparison purposes. It is shown that the non-linear SMO is more accurate than the other two methods. The robustness and superior performance of the SMO are demonstrated using both simulation and experimental results. A specially designed test rig is used for accurate control and measurement of track slips during the experimental validation of the proposed observer.