Robust path following control for wheeled robots via sliding mode techniques

The techniques of filtering and merging data coming from several sensors allow to localize a mobile robot in its environment with a precision which can be evaluated. However, as the localization error cannot be neglected, the design of robust closed-loop controller for wheeled robots constitutes a difficult problem. We present here a path following feedback controller robust with respect to localization error. The model is a dynamic extension of the usual kinematic model of a car, in the sense that the path curvature error is considered as a new state variable. The control inputs are respectively the linear velocity and the derivative of the curvature. We determine a variable structure control with sliding mode to stabilize the vehicle's motion around the reference path in the nominal case. Then, we prove that the system remains stable when the state feedback is computed from the estimated values instead of the exact ones. We show that the regulation error is contained in a compact attractive domain when the system has reached its steady state. From this domain, one can easily compute a security margin to guarantee obstacle avoidance during the path following process. Experimental results are presented at the end of the paper.