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基于采样的机器人路径规划中后处理的双向插值方法。

A Bidirectional Interpolation Method for Post-Processing in Sampling-Based Robot Path Planning.

机构信息

Department of Artificial Intelligence, Dongguk University, Seoul 04620, Korea.

Department of Computer Science and Engineering, Dongguk University, Seoul 04620, Korea.

出版信息

Sensors (Basel). 2021 Nov 8;21(21):7425. doi: 10.3390/s21217425.

DOI:10.3390/s21217425
PMID:34770732
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8587826/
Abstract

This paper proposes a post-processing method called bidirectional interpolation method for sampling-based path planning algorithms, such as rapidly-exploring random tree (RRT). The proposed algorithm applies interpolation to the path generated by the sampling-based path planning algorithm. In this study, the proposed algorithm is applied to the path created by RRT-connect and six environmental maps were used for the verification. It was visually and quantitatively confirmed that, in all maps, not only path lengths but also the piecewise linear shape were decreased compared to the path generated by RRT-connect. To check the proposed algorithm's performance, visibility graph, RRT-connect algorithm, Triangular-RRT-connect algorithm and post triangular processing of midpoint interpolation (PTPMI) were compared in various environmental maps through simulation. Based on these experimental results, the proposed algorithm shows similar planning time but shorter path length than previous RRT-like algorithms as well as RRT-like algorithms with PTPMI having a similar number of samples.

摘要

本文提出了一种基于双向插值的后处理方法，用于基于采样的路径规划算法，如快速探索随机树（RRT）。所提出的算法对基于采样的路径规划算法生成的路径进行插值。在本研究中，将所提出的算法应用于 RRT-connect 生成的路径，并使用六个环境地图进行验证。从视觉和定量两方面确认，与 RRT-connect 生成的路径相比，不仅路径长度，而且分段线性形状都有所减小。为了检查所提出算法的性能，通过仿真在各种环境地图中比较了可见性图、RRT-connect 算法、三角 RRT-connect 算法和中点插值的三角形后处理（PTPMI）。基于这些实验结果，所提出的算法显示出与类似 RRT 的算法相似的规划时间，但路径长度更短，并且与具有类似样本数量的 PTPMI 的类似 RRT 的算法相比，具有相似的路径长度。

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本文引用的文献

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