TRAJECTORY TRACKING WITH COLLISION AVOIDANCE FOR AUTONOMOUS SURFACE VESSELS IN DYNAMIC OBSTACLE ENVIRONMENTS USING TRAJECTORY PREDICTION AND ADAPTIVE SLIDING MODE CONTROL

Abstract

This article proposes an integrated control framework to simultaneously address trajectory tracking and collision avoidance problems for autonomous surface vessels operating in environments with dynamic obstacles. The proposed framework combines a collision-risk assessment mechanism based on the Time to Closest Point of Approach (TCPA), Distance at Closest Point of Approach (DCPA), and Collision Risk Index (CRI) with an Adaptive Sliding Mode Control (ASMC) scheme. The TCPA, DCPA, and CRI indicators are utilized to evaluate collision risk and coordinate the online modification of the reference trajectory, thereby generating a safe reference trajectory for the ASMC controller to accomplish both trajectory tracking and collision avoidance tasks. Meanwhile, the ASMC controller ensures accurate tracking performance and robustness against environmental disturbances and model uncertainties without requiring prior knowledge of the disturbance upper bounds. Simulation results obtained from a marine vessel model demonstrate that the proposed method can successfully avoid collisions in dynamic-obstacle scenarios while maintaining trajectory-tracking accuracy and overall system stability under environmental disturbances.