Unscented Kalman Filter-based adaptive tracking control for wheeled mobile robots in the presence of wheel slipping

Abstract

A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown longitudinal and lateral slipping. A kinematic model of a tracked wheeled mobile robot (WMR) is established in this paper, in which both longitudinal and lateral slipping is considered and processed as three time-varying parameters. The Unscented Kalman Filter (UKF) with the low pass filter is then introduced for real-time estimation of the slipping parameters online. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov theory. Simulation results show the effectiveness and robustness of the proposed method.