Path Planning for Unmanned Sailboats using Improved Potential Field and A* Algorithm
Siju Yuan, Zhongben Zhu, Yifan Xue, Xiaokai Mu, Hongde Qin, Guiqiang Bai · 2024
Unmanned sailboats, propelled by wind energy, offer an effective means for large-scale ocean-atmosphere interface observation. Due to the unpredictable and uncontrollable nature of marine winds, coupled with non-navigable zones arising from the dynamic characteristics of sailboats, path planning for sailboats presents additional challenges distinct from conventional unmanned surface vehicles (USV). The paper presents a two-layer path planning method that utilizes the improved A* algorithm and artificial potential field (APF). The heuristic function of the A* algorithm incorporates the dynamic characteristics of the sailboat, employing an increased number of search profiles to efficiently determine the globally optimized path to the target point. Simultaneously, a novel concept referred as the “boundary potential field” is proposed to address the sailboat's rounding problem. Additionally, based on the VPP of the sailboat, the concept of velocity potential field is proposed to realize the planning of the fastest local path. To facilitate autonomous obstacle avoidance, an elliptical obstacle avoidance potential field is presented, considering the sailboat's dynamic characteristics and hull shape. Finally, the effectiveness of the proposed method is validated through simulations employing a four-degree-of-freedom model in a simulated environment featuring wind in the ocean.