An Integrated Trajectory Planning and Motion Control Strategy for Autonomous Berthing of Underactuated Uncrewed Surface Vehicles

Autonomous berthing is a crucial part of achieving full autonomy and intelligence for unmanned surface vehicles (USVs). While some research addresses USV planning and control in open-water scenarios, the autonomous berthing of underactuated USVs still faces significant challenges, including limited space constraints, underactuated dynamics, and environmental disturbances. To address these issues, this paper proposes an integrated dual-loop trajectory planning and motion control strategy for autonomous berthing of underactuated USVs. In the outer-loop planner, a nonlinear model predictive control problem is formulated to generate the optimal trajectory over a finite prediction horizon, ensuring that both state and input constraints are satisfied. To mitigate the computational costs associated with continuous replanning, an adaptive trajectory replanning strategy is employed, updating the reference trajectory only when tracking errors exceed the predefined threshold. The innerloop tracking controller then follows the reference trajectory calculated by the outer loop. It combines adaptive disturbance observer compensations and robust feedback with linear feedback terms to enhance tracking precision and provide high antidisturbance capabilities. Comprehensive simulations and experiments have been implemented to validate the effectiveness of the proposed method.