This paper is focused on the design of a control strategy for the path tracking of off-road mobile robots acting at high speed. In order to achieve high accuracy in such a context, uncertain and fast dynamics have to be explicitly taken into account. Since these phenomena (grip conditions, delays due to inertial and low-level control properties) are hardly measurable directly, the proposed approach relies on predictive and observer-based adaptive control techniques. In particular, the adaptive part is based on an observer loop, taking advantage of both kinematic and dynamic vehicle models. This multimodel based adaptive approach permits to adapt on-line the grip conditions (represented by cornering stiffnesses), enabling highly reactive sideslip angles observation and then accurate path tracking. The relevance of this approach is investigated through full scale experiments.

In mobile robot path tracking applications, an autonomous vehicle is steered to stay as close as possible to a desired path. If lateral wheel slip is an important variable, as it is the case at high speed and due to low tire-ground friction in off-road applications, limits of the steering actuators, the major input constraints of the system, have a major influence on the tracking control performance. This paper presents an algorithm to control the longitudinal velocity, a secondary control variable, of a mobile robot in order to respect the boundedness of the steering angle, and thus to improve the vehicle safety. The applicability of the algorithm has been verified through experiments with an off-road mobile robot.

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