Collision-free Trajectory Planning for Autonomous Surface Vehicle

TL;DR

This paper presents a novel two-stage trajectory planning method for autonomous surface vehicles that ensures collision avoidance, fuel efficiency, and adherence to vehicle dynamics through sampling-based path search and kinodynamic optimization.

Contribution

It introduces a decoupled planning approach combining sampling-based path search with numerical optimization, including a sailing corridor method for safety and fuel-efficient trajectory generation.

Findings

The method successfully generates smooth, collision-free trajectories in simulation.

Trajectories are optimized for fuel efficiency and safety.

Simulation results confirm the effectiveness of the proposed approach.

Abstract

In this paper, we propose an efficient and accurate method for autonomous surface vehicles to generate a smooth and collision-free trajectory considering its dynamics constraints. We decouple the trajectory planning problem as a front-end feasible path searching and a back-end kinodynamic trajectory optimization. Firstly, we model the type of two-thrusts under-actuated surface vessel. Then we adopt a sampling-based path searching to find an asymptotic optimal path through the obstacle-surrounding environment and extract several waypoints from it. We apply a numerical optimization method in the back-end to generate the trajectory. From the perspective of security in the field voyage, we propose the sailing corridor method to guarantee the trajectory away from obstacles. Moreover, considering limited fuel ASV carrying, we design a numerical objective function which can optimize a fuel-saving trajectory. Finally, we validate and compare the proposed method in simulation environments and the results fit our expected trajectory.