Slip Estimation Using the Unscented Kalman Filter for the Tracking Control of Mobile Robots

Abstract. Research on autonomous navigation for tracked mobile robots operating in unstructured environments has received renewed attention in the last years due to its increasing use in tasks as forestry, mining, agriculture, military applications and space exploration. For these tasks, the slip phenomena is an important factor that must be taken into account during the control design. If the slip is not considered, the control objective may not be completed and a stable system may even become unstable. Accurate estimation of the slip is essential for the implementation of efficient control strategies. This paper shows that the longitudinal slip of the tracks can be estimated from the robot pose and velocity using the unscented Kalman filter (UKF). A control strategy that uses the estimation of the slip is proposed to achieve the trajectory tracking objective. The control strategy is based on the kinematic and dynamic models which include the longitudinal slip of the left and right tracks as two unknown parameters. Numerical results show the performance of the proposed control strategy.