人工智能鱼是鱼类仿生学研究中的热点，针对三维虚拟海洋环境中人工智能鱼路径规划低效的问题，提出一种基于改进A*算法的人工智能鱼路径规划方法。首先，在A*算法路径搜索时每选取一个路径节点后实行OPEN列表的清空操作，然后使用碰撞检测算法筛选出寻优路径中不必要的路径节点，进一步优化鱼类的游泳路径。结果显示：改进的A*算法相较于传统的A*算法在算法效率相当的同时，所寻得的路径长度减少了5%。研究表明，使用改进的A*算法可以在虚拟海洋三维空间中精准地规划出智能鱼的游泳路径，提高智能鱼仿真的真实性，为渔业中的鱼类仿真模拟提供一种新的思路。

 Artificial fish is a hot spot in fish bionics research. Aiming at the low efficiency of artificial intelligence fish path planning in three-dimensional virtual marine environment, an artificial intelligence fish path planning method based on improved A* algorithm is proposed. First and foremost, after each path node is selected in the path search of A* algorithm, the OPEN table is emptied. Then, collision detection algorithm is used to screen out unnecessary path nodes in the optimization path to further optimize the fish swimming path. The results show that compared with the traditional A* algorithm, the improved A* algorithm has the same efficiency, and the path length is reduced by 5%. The research shows that the improved A* algorithm can accurately plan the swimming path of artificial intelligence fish in the three-dimensional virtual ocean space, improve the authenticity of artificial intelligence fish simulation and provide a new idea for the simulation of fish in fishery.