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基于拟合优先搜索的多场景自适应改进A*算法

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针对传统A*算法存在遍历节点数多、转折角度大和搜索速度慢的问题,提出基于拟合优先搜索的多场景自适应改进A*算法。首先,引入父节点的启发距离以减少遍历节点数和提高搜索速度,并量化场景地图信息,利用自适应控制原理实现启发权重的适时调整,以增强算法鲁棒性;其次,采用拟合优先搜索策略,进一步增强算法的启发性;接着,通过局部剪枝和冗余节点删除对路径进行平滑处理,减少遍历节点数和转折角度;最后,进行仿真测试。测试结果表明,所提算法遍历节点数更少、转折角度更小、搜索速度更快。
A multi-scene adaptive A* algorithm based on fitting-first search
Aiming at the problems of large number of traversal nodes,large turning angle,and slow search speed of the traditional A* algorithm,a multi-scene adaptive improvement A* algorithm based on fitting-first search is proposed.Firstly,the heuristic distance of the parent node is introduced to re-duce the number of traversal nodes and improve the search speed,the scene map information is quanti-fied,and the adaptive control principle is used to achieve the timely adjustment of the heuristic weight to enhance the robustness of the algorithm.Secondly,the heuristic strategy of fitting-first search is used to further enhance the heuristic of the algorithm.Thirdly,the path is smoothed through local pruning and redundant node deletion to reduce the number of traversed nodes and the turning angle.Finally,a simu-lation test is carried out on Matlab,and the test results show that the proposed algorithm has fewer traversed nodes,smaller turning angle,and faster search speed.

A* algorithmpath planningadaptivefitting-firstpath smoothing

沈克宇、游志宇、刘永鑫

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西南民族大学电气工程学院,四川成都 610225

A*算法 路径规划 自适应 拟合优先 路径平滑

成都市科技项目西南民族大学中央高校基本科研业务费专项资金

2021-RK00-00079-ZF2021101

2024

计算机工程与科学
国防科学技术大学计算机学院

计算机工程与科学

CSTPCD北大核心
影响因子:0.787
ISSN:1007-130X
年,卷(期):2024.46(1)
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