LAUSR

This article studies the problem of obstacle-avoidance tracking control for a class of uncertain nonlinear robot systems in multiple-dynamic-obstacles environment. The main challenge focuses on how to simultaneously ensure tracking performance and obstacle avoidance. The existing collision-avoidance tracking control schemes cannot guarantee the tracking performance inside the obstacle detection region, since the use of additive Lyapunov-barrier function (LBF) generates the dynamic mismatching. To overcome this difficulty, a novel integral-multiplicative LBF is constructed. The adaptive mechanism is designed to compensate for the mismatching uncertainties. By incorporating the barrier function into backstepping procedure, a secure adaptive tracking control scheme is proposed. Compared with the existing results, the proposed control scheme can simultaneously achieve the obstacle avoidance and tracking performance regardless of being inside the obstacle sensing region and unknown nonlinear uncertainties.