基于跳点搜索和剪枝的轮式机器人路径规划改进A星算法

Hongqian Huang, Yanzhou Li, Qing Bai
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引用次数: 4

摘要

轮式机器人在食品配送、房间消毒等广泛领域广受欢迎。它们可以降低劳动力成本,保护人类健康免受感染,等等。考虑到躲避障碍物的需要,机器人的路径规划是一个基本模块。到目前为止,A*算法已被广泛使用,但它承受了很大的内存开销,并提供了一个次优路径。因此,我们提出了一种改进的A*算法,该算法结合了跳点搜索方法和剪枝思想。具体来说,跳点搜索方法降低了开放列表的占用率。通过修剪可以缩短路径的长度。仿真实验证明了改进的有效性和实用性。
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An improved A star algorithm for wheeled robots path planning with jump points search and pruning method
Wheeled robots enjoy popularity in extensive areas such as food delivery and room disinfection. They can lower labor costs, protect human health from infection, and so on. Given the need to avoid obstacles, the path planning of robots is an elementary module. The A* algorithm has been widely used thus far, but it suffers much memory overhead and provides a suboptimal path. Therefore, we propose an improved A* algorithm with the jump point search method and pruning idea. Specifically, the jump point search method reduces the occupancy rate of the open list. The shorter length of the path can be achieved by pruning. Simulation experiments proved that the improvement was effective and practical.
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