Collision avoidance control of an automated guided vehicle based on hierarchical trajectory planning and fixed-time prescribed adaptive sliding mode

In this paper, a hybrid collision avoidance control (CAC) approach including trajectory planner and controller is proposed for an automated guided vehicle (AGV). Firstly, by combing the improved A* and timed-elastic-band method, a hierarchical trajectory planner is developed to realize the flexible collision avoidance trajectory planning of AGV. Subsequently, the trajectory controller is constructed to achieve the accurate tracking of the planned trajectory. Since the controller is developed based on a faster fixed-time stable system and a prescribed performance function, both the fixed-time and prescribed bounded convergences of the trajectory tracking system can be realized. In addition, a newly designed sliding mode filter-based nested adaptive law is adopted in the controller to update the control gain, thereby releasing the prior bound information of AGV unknown disturbance and minimizing control chattering. The global stability and prescribed convergence of the system are proved by Lyapunov theory. Finally, the effectiveness and merits of the presented CAC approach in flexible trajectory planning and accurate tracking are demonstrated by experimental validations on an AGV.