Warm-started Semionline Trajectory Planner for Ship's Automatic Docking (Berthing)

TL;DR

This paper presents a warm-started semionline trajectory planning method for ship docking that reduces computation time and improves safety by integrating wind prediction, boundary constraints, and an almost-globally optimal offline solution.

Contribution

It introduces a novel warm-start approach combined with wind prediction and boundary constraints for efficient, safe ship docking trajectory optimization under disturbances.

Findings

Warm start significantly speeds up computation.

The method produces safer, collision-free trajectories.

Inclusion of wind prediction improves accuracy.

Abstract

In the usual framework of control, a reference trajectory is needed as the set point for a feedback controller. This reference trajectory can be generated by solving a trajectory optimization problem. This problem is a continuous optimal control problem (OCP) that is transcribed into a finite-dimensional nonlinear optimization problem (NLP) and solved by SQP. For an underactuated conventional vessel, the mathematical model can be very intricate, hence the NLP itself. This causes significant computational time. This article demonstrates that the balance between the feasibility of the reference trajectory and the computational time can be achieved for an underactuated vessel in a disturbed and restricted environment. This is done by: (1) using an almost-globally optimal offline solution as a warm start in a semionline trajectory optimization to speed up the calculation, (2) including the prediction of wind dynamics, and (3) representing the ship as a rigid body and using a predefined boundary to generate the necessary spatial constraints via a point-in-polygon method that ensure a collision-free trajectory in a nonconvex region. Incorporation of these three things maintains a safe and dynamically feasible trajectory where the warm start gives a considerable computational speedup and better results than that without a warm start.