基于自适应步长策略的A*算法路径规划优化
作者:
作者单位:

南京信息工程大学自动化学院

中图分类号:

TP242

基金项目:

“333工程”科研项目科研资助立项项目(BRA2020067)


Path optimization of A* algorithm based on adaptive step size strategy
Author:
Affiliation:

School of Automation,Nanjing University of Information Science and Technology,Nanjing

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    摘要:

    针对A*算法求解路径轨迹耗时长、内存占用大等问题,本文提出了一种基于自适应步长策略改进A*算法。首先,根据当前点与终点的位置关系,设定寻路方向的优先级顺序,减少不合理方向上的冗余规划计算量。其次,修改到达终点的判断条件,可在轨迹规划时实现路径的跳跃。再次,针对A*算法轨迹规划效率低的问题,提出自适应步长策略。最后,针对内存占用大,以及面对大地图时可能出现的内存溢出问题,提出了八方向搜索法。实验结果表明,相较于原始的A*算法,改进的A*算法在轨迹规划效率上获得了极大的提升,同时内存占用大的问题也得到了很好的解决。

    Abstract:

    Aiming at the problems of long time-consuming and large memory consumption of A* algorithm in solving path trajectory, this paper proposes an improved A* algorithm based on adaptive step. Firstly, the priority order of the search direction is set according to the position relationship between the current point and the end point, reducing the redundant planning calculation on unreasonable directions. Secondly, the judgment condition for reaching the end point is modified to achieve path jumping during trajectory planning. Thirdly, an adaptive step size strategy is proposed to improve the efficiency of A* algorithm in trajectory planning. Finally, an eight-directional search method is proposed to address the issues of large memory usage and possible memory overflow when facing large maps. Experimental results show that compared with the original A* algorithm, the improved A* algorithm greatly improves the efficiency of trajectory planning, and the problem of large memory usage is also well solved.

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付雄,李涛.基于自适应步长策略的A*算法路径规划优化[J].南京信息工程大学学报,,():

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  • 收稿日期:2023-02-18
  • 最后修改日期:2023-04-10
  • 录用日期:2023-04-14

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