基于改进A*的特殊环境下移动机器人路径规划研究

Ren Yiyue, Xiaoru Song, Gao Song
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引用次数: 4

摘要

针对A*算法在障碍物密度大的环境中存在的内存开销大、计算时间长等问题,提出了一种基于静态权值法与跳点搜索相融合的算法。静态权值法改进了启发式函数,限制了搜索空间,减少了暴力搜索。实验结果表明,与传统的A*算法相比,跳跃点搜索减少了访问节点数,加快了搜索速度。因此,该算法可以满足特殊环境下快速寻径的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Path Planning of Mobile Robot Based on Improved A* in Special Environment
Aiming at the problems of A* algorithm in a large environment with density of obstacles, such as large memory overheads, long calculation times, an novel method based on the fusion of static weight method and jump point search is proposed in this paper. Static weight method improves heuristic function, then the search space is limited and brute force search is reduced. Jump point search filters key points, then unnecessary nodes are reduced and search speed is accelerated The experimental results demonstrate that compared with traditional A* algorithm, the number of invisited nodes is reduced, and the search speed is accelerated. Therefore, the proposed algorithm can meet the requirements of fast path finding in special environments.
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