An event-triggered trajectory planning and tracking scheme for automatic berthing of unmanned surface vessel

Abstract

This study proposes a trajectory planning and tracking scheme for the fully actuated USV's automatic berthing. First, a three-degree-of-freedom model (3-DOF) of USV is employed, considering model uncertainty, actuator saturation, and environmental disturbances. Moreover, an A* algorithm with the Bezier curve (AB) approach is proposed to plan the smooth berthing trajectory. To make the velocity of the USV converge to zero at the berth, an interpolation method is proposed to densify the waypoints at the end of the berthing trajectory. Most of the previous studies about USV's tracking control pay little attention to real-time performance, which may increase the computational cost of the control system and affect its stability. Therefore, to improve the computational performance during the USV's berthing, an event-triggered adaptive horizon model predictive control (ETAHMPC) method is proposed. Comparative simulation experiments are performed in two scenarios to verify the effectiveness and superiority of the proposed ETAHMPC scheme. The results show that the proposed scheme can effectively reduce computational costs while ensuring control performance.