An efficient layered robot path planning approach based on MOPSO algorithm

Han Wu, Huiliang Shang
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引用次数: 1

Abstract

A layered path planning approach is designed to find a collision free and global optimal path from the start position to goal position in static environment. In the first two levels, called preprocessing, Delaunay triangulation and Dijkstra’s algorithm are applied to generate the initial approximate optimal paths. Then considering two objectives, minimizing the path length and maximizing the path smoothness, the improved multi-objective particle swarm optimization is used to optimize the initial paths in the third level. Various experimental results in different environments show that the proposed layered planning method can avoid the local optimal path and accelerate the convergence.
基于MOPSO算法的高效分层机器人路径规划方法
设计了一种分层路径规划方法,寻找静态环境下从起始位置到目标位置的无碰撞全局最优路径。在前两个阶段,称为预处理,使用Delaunay三角剖分和Dijkstra算法来生成初始的近似最优路径。然后考虑路径长度最小化和路径平滑最大化两个目标,采用改进的多目标粒子群算法对第三层的初始路径进行优化。在不同环境下的实验结果表明,分层规划方法可以避免局部最优路径,加快收敛速度。
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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