粒子群算法优化机器人路径规划的研究

巫光福; 万路萍

doi:10.13433/j.cnki.1003-8728.20200465

粒子群算法优化机器人路径规划的研究

doi: 10.13433/j.cnki.1003-8728.20200465

江西理工大学信息工程学院，江西赣州　341000

基金项目: 国家自然科学基金项目（11461031）、江西省自然科学基金项目（20181BBE58018）、江西省教育厅科技计划项目（GJJ180442）及江西省教育厅科技重点项目（GJJ170492）

详细信息

作者简介:
巫光福（1977−），副教授，博士，研究方向为信息论与编码、人工智能等，wuguangfu@126.com

中图分类号: TP242.6
计量
- 文章访问数: 101
- HTML全文浏览量: 172
- PDF下载量: 22
- 被引次数: 0
出版历程
- 收稿日期: 2020-09-05
- 刊出日期: 2023-02-04

Research on Improved Particle Swarm Optimization Algorithm for Robot Path Planning

School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, Jiangxi, China

摘要

摘要: 针对标准粒子群算法在移动机器人路径规划问题上存在的收敛速度慢、易陷入“早熟”现象以及路径不平滑等缺点，对粒子群优化算法进行改进，该方法在粒子陷入局部最优值时，对全局最优粒子的速度进行了轻微的干扰，从而提高收敛速度。为了平衡局部和全局搜索能力，提出了非线性惯性权重。最后提出一个考虑路径最短和平滑性的适应度函数。仿真结果表明，在一个动态环境中，改进之后的粒子群优化算法收敛快，并能避开障碍物，寻找到符合要求的最优路径。
- 粒子群算法 /
- 非线性惯性权重 /
- 平滑性 /
- 路径规划
Abstract: Aiming at the shortcomings of the standard particle swarm algorithm in the path planning of mobile robots, such as slow convergence, easy to fall into the "premature" phenomenon, and unsmooth path, the particle swarm optimization algorithm is improved in this paper. When the particles fall into the local optimal value, this improved method can slightly perturb the speed of the global optimal particle to increase the convergence speed. In order to balance the local and global search capabilities, nonlinear inertia weights are proposed. Finally, a fitness function considering the shortest path and smoothness is also proposed. The simulation results show that in a dynamic environment, the improved particle swarm optimization algorithm converges quickly, avoids obstacles, and finds the optimal path that meets the requirements.
- particle swarm algorithm /
- nonlinear inertia weights /
- smoothness /
- path planning

HTML全文

图 1 环境模型

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图 2 标准粒子群算法

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图 3 一个粒子位置移动概念

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图 4 两种惯性权重的变化曲线

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图 5 目标点与两个连续位置的夹角

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图 6 障碍物个数为5的路径寻优结果

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图 7 障碍物个数为8的路径寻优结果

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图 8 改进PSO算法路径寻优结果

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图 9 基本PSO的路径寻优结果

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表 1 路径规划的实验结果比较

障碍物个数平均迭代次数搜索成功率η/%
本文
方法基本
PSO 本文方法基本PSO

5 2 3 96 94
8 5 8 92 91
10 11 19 90 86

下载: 导出CSV

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