基于改进A*算法的无人机路径规划研究
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1.云南民族大学电气信息工程学院 昆明 650000; 2.云南民族大学无人自主系统研究院 昆明 650000

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V249;V279;TP18

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国家自然科学基金(61963038)项目资助


Research on UAV path planning based on improved A* algorithm
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1.School of Electrical and Information Engineering,Yunnan Minzu University,Kunming 650000, China; 2.Unmanned Autonomous Systems Institute, Yunnan Minzu University,Kunming 650000, China

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    摘要:

    针对传统A*算法在无人机路径规划时效率低下、路径点存在大量冗余,且路径转折较多的缺点,提出一种基于双向机制的改进A*算法。首先引入双向搜索机制,分别以对向搜索的起点作为终点,然后判断终点位于起点的象限进行双定向搜索,从而提高搜索效率。最后引入路径平滑策略,将双定向搜索获取的初始路径进行平滑处理,减少冗余路径点和转折点。通过MATLAB平台对传统A*算法和改进A*算法进行对比实验,实验结果表明,相比于传统A*算法,提出的改进A*算法,路径规划时间平均减少了61.61%,路径点平均减少了83.09%,路径转折点平均减少了46.97%,能够有效提高无人机工作效率,生成平滑路径。

    Abstract:

    Aiming at the shortcomings of the traditional A* algorithm in UAV path planning, such as low efficiency, a large number of redundant path points, and many path transitions, an improved A* algorithm based on two-way mechanism is proposed. First, a bidirectional search mechanism is introduced, which takes the starting point of the opposite search as the end point, and then determines that the end point is located in the quadrant of the starting point for bidirectional search, so as to improve the search efficiency. Finally, the path smoothing strategy is introduced to smooth the initial path obtained by the bi directional search to reduce redundant path points and turning points. The traditional A* algorithm and the improved A* algorithm are compared through the MATLAB platform. The experimental results show that compared with the traditional A* algorithm, the improved A* algorithm proposed reduces the average path planning time by 61.61%, path points by 83.09%, and path turning points by 46.97%, which can effectively improve the working efficiency of UAVs and generate smooth paths.

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唐嘉宁,彭志祥,李孟霜,刘志聪,谢翠娟.基于改进A*算法的无人机路径规划研究[J].电子测量技术,2023,46(8):99-104

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  • 在线发布日期: 2024-02-07
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