摘要
为了解决复杂环境下A~*寻路算法存在搜索节点多,搜索时间长,路径曲折的问题,提出了一种改进的A~*算法。首先,在具有障碍物的栅格地图中引入象限的概念,通过限制当前节点只朝目标节点所处的一个象限进行节点扩展,有效降低了寻路过程中搜索的节点数量。其次,在估价函数中考虑了AGV行驶和转向时间消耗成本,从而有效的搜索最短时间路径。通过仿真实验分析比较了文中算法与A~*算法以及另一种改进A~*算法的搜索性能。仿真结果表明,文中算法能有效减少寻路过程中的搜索节点数和转向次数,提高了路径搜索效率和平滑度。
In order to solve the problems of A~* algorithm in complex environment, such as large number of search nodes, long search time, search path twist and turns etc, an improved A~* algorithm is presented. Firstly, the quadrant concept is introduced in a grid map with obstacles, and the number of searching nodes in the path finding process are effectively reduced by limiting the current node to expand only toward one quadrant where the target node is located. Secondly, the travelling and turning time costs are added into the evaluation function, so that the shortest-time path can be searched effectively. The analysis and comparison between the proposed algorithm, traditional A~* algorithm and another improved A~* method were then given in the simulation experiments. The experiment results show that the proposed algorithm effectively reduces the number of search nodes and turning times in the path planning, improves the path search efficiency and smoothness.
引文
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