Research on path-planning of particle swarm optimization based on distance penalty

Dechen Yuan
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Abstract

Nowadays, designing the optimal path in the complex urban environment is still a significant problem. This paper studies an application of path planning using Particle Swarm Optimization. The grid method is used to divide the environment to fit the implementation of particle swarm optimization. The objective function evaluates the distance of the path, and the penalty is involved to avoid obstacles along the path. Finally, the particle swarm optimization is used in two path planning problems regarding emergency and common vehicles to design the optimal path.
基于距离惩罚的粒子群优化路径规划研究
目前,在复杂的城市环境中设计最优路径仍然是一个重要的问题。本文研究了粒子群算法在路径规划中的应用。采用网格法对环境进行划分,以适应粒子群优化的实现。目标函数评估路径的距离,并涉及到避免路径上障碍物的惩罚。最后,将粒子群算法应用于应急车辆和普通车辆两个路径规划问题,设计出最优路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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