A set-based approach for detecting faults of a remotely controlled robotic vehicle during a trajectory tracking maneuver

This paper addresses the problem of fault detection for a remotely controlled Differential Drive Mobile Robot (DDMR) during trajectory tracking maneuvers. The proposed solution involves two steps. The first step, performed offline, consists of generating a feasible trajectory for the DDMR subject to unknown but bounded external disturbances. To this end, the dynamics of the closed-loop trajectory tracking error are first described using an uncertain system with norm-bounded uncertainty. The optimal feasible trajectory is obtained by a recursive algorithm that involves solving some SDP optimization problems with LMIs constraints. In the second step, which is performed online, the feasibility property of the computed trajectory is exploited to detect faults during the tracking maneuvers. In order to validate the proposed approach, an extensive experimental test campaign was conducted using the Jaguar V4 Dr.Robot platform.