一种基于RRT的改进路径规划算法

Qiongwei Zhang, Lunxing Li, Liaomo Zheng, Beibei Li
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引用次数: 4

摘要

快速探索随机树(RRT)算法可以通过随机抽样快速完成路径规划任务。然而,在RRT节点的选择过程中只考虑了部分成本,在某些环境下可能会导致效率低下。针对这一问题,本文提出了一种基于快速扩展随机树算法的混合路径规划算法。该算法在RRT随机展开搜索的基础上引入了启发式搜索思想,保证了搜索的整体效率。实验表明,在某些环境下,该算法可以在更短的时间内规划出更有效的路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Path Planning Algorithm Based on RRT
The rapidly-exploring random tree (RRT) algorithm can quickly complete the task of path planning through random sampling. However, only part of the cost is considered in the selection process of RRT nodes, which may cause inefficiency in some environments. In response to this problem, this paper proposes a new hybrid path planning algorithm based on the rapid expansion of random tree algorithm. This algorithm introduces heuristic search ideas on the basis of RRT's random expansion search to ensure the overall efficiency of the search. Experiments show that in some environments, the algorithm can plan a more efficient path in a shorter time.
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