基于A*和强化学习的风电场水区路径规划算法

Tianqi Zha, Lei Xie, Jiliang Chang
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引用次数: 3

摘要

近年来,由于风力发电资源高效、无污染,海上风电场规模不断扩大。然而,在相应的风电场海域引入了许多设施,导致船舶航行难度越来越大。因此,在风电场面积不断增大的情况下,根据相应的起止点规划安全高效的船舶航行路径是十分重要的。本文提出了一种基于a *算法和强化学习混合方法的路径规划算法,可为风电场海域规划有效的避撞路径。将该方法应用于某风电场船舶路径规划仿真,验证了该方法的可行性。最后表明,该方法对船舶在风电场水域航行具有普遍的参考意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wind farm water area path planning algorithm based on A* and reinforcement learning
In recent years, the scale of offshore wind farms is increasing because of the high efficiency and pollution-free wind power resources. However, the introduction of many facilities in the corresponding wind farm sea area has led to the increasing difficulty of ship navigation. Therefore, it is very important to plan safe and efficient driving path according to the corresponding starting and ending points for the navigation of ships in the increasing wind farm area. In this paper, a path planning algorithm based on the hybrid method of A* algorithm and reinforcement learning is proposed, which can plan an effective collision avoidance path for the sea area of wind farm. Then the method is used to simulate the ship’s path planning in a wind farm, which proves the feasibility of the method. Finally, it shows that the method has universal reference significance for ship navigation in the wind farm waters.
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