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Artificial intelligence pathfinding based on Unreal Engine 5 hexagonal grid map

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成果类型:
会议论文
作者:
Hongbo Xing;Mengyao Chai;Yaju Song
作者机构:
[Hongbo Xing; Mengyao Chai; Yaju Song] College of Physics and Electronic Engineering, Hengyang Normal University, Hengyang, China
语种:
英文
关键词:
Unreal Engine 5;Artificial intelligence pathfinding algorithm;Hexagonal grid map
年:
2024
页码:
1708-1711
会议名称:
2024 4th International Conference on Neural Networks, Information and Communication Engineering (NNICE)
会议论文集名称:
2024 4th International Conference on Neural Networks, Information and Communication Engineering (NNICE)
会议时间:
19 January 2024
会议地点:
Guangzhou, China
出版者:
IEEE
ISBN:
979-8-3503-9438-2
机构署名:
本校为第一机构
院系归属:
物理与电子工程学院
摘要:
This paper proposes an A* artificial intelligence pathfinding algorithm based on the hexagonal grid map of Unreal Engine 5. This algorithm utilizes the rich tools and resources provided by Unreal Engine 5 to evaluate each node through a heuristic function, thus finding the shortest path. Test results show that this algorithm not only can quickly find the shortest path, but also can effectively avoid obstacle grids, with advantages such as high efficiency, flexibility, and scalability. This research result has high practical value for solving pathfinding problems on hexagonal grid maps and can ...

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