Wind farm water area path planning algorithm based on A* and reinforcement learning
Tianqi Zha, Lei Xie, Jiliang Chang · 2019
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.