Robot path planning based on A*algorithm and genetic algorithm

Tang Xiang Rong, Xu Hong Mei
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Abstract

The traditional algorithm of path planning is slow in time, heavy in calculation and large in storage space. Taking the medical service robot of Raytheon hospital(in Wuhan) as an example, optimizing its path planning, this paper proposes a combination algorithm based on genetic algorithm and A* algorithm, and two-dimensional modeling of the hospital map was carried out by raster method. Through simulation experiments, comparison with traditional algorithm and model tests, the feasibility and effectiveness of the combined algorithm are confirmed. Meanwhile, the efficiency of path planning is improved, the step size is optimized by 23%, the time is increased by 135%, and the calculation amount is reduced, and the calculation time and storage space are reduced.
基于A*算法和遗传算法的机器人路径规划
传统的路径规划算法存在时间慢、计算量大、存储空间大等问题。本文以武汉雷神医院医疗服务机器人为例,对其路径规划进行优化,提出了一种基于遗传算法和a *算法的组合算法,并采用栅格法对医院地图进行二维建模。通过仿真实验、与传统算法的对比和模型测试,验证了该组合算法的可行性和有效性。同时提高了路径规划的效率,优化步长23%,时间增加135%,减少了计算量,减少了计算时间和存储空间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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