A COMPARATIVE STUDY FOR WHEELED MOBILE ROBOT PATH PLANNING BASED ON MODIFIED INTELLIGENT ALGORITHMS

M. M. A. Nayar, K. Dagher, E. A. Hadi
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引用次数: 2

Abstract

From the time being, there are even instances for application of mobile robots in our lifelike in home, schools, hospitals, etc. The goal of this paper is to plan a path and minimizing thepath lengths with obstacles avoidance for a mobile robot in static environment. In this work wedepict the issue of off-line wheeled mobile robot (WMR) path planning, which best route forwheeled mobile robot from a start point to a target at a plane environment represented by 2-Dwork space. A modified optimization technique to solve the problem of path planning problemusing particle swarm optimization (PSO) method is given. PSO is a swarm intelligence basedstochastic optimization technique which imitate the social behavior of fish schooling or birdflocking, was applied to locate the optimum route for mobile robot so as to reach a target.Simulation results, which executed using MATLAB 2014 programming language, confirmedthat the suggested algorithm outperforms the standard version of PSO algorithm with the sameenvironment conditions by providing the shortest path for mobile robot.
基于改进智能算法的轮式移动机器人路径规划比较研究
从那时起,甚至有移动机器人在我们逼真的家庭、学校、医院等中的应用实例。本文的目标是为移动机器人在静态环境中规划路径并在避障的情况下最小化路径长度。在这项工作中,我们讨论了离线轮式移动机器人(WMR)路径规划问题,该问题是轮式移动机器人在二维空间表示的平面环境中从起点到目标的最佳路径。提出了一种利用粒子群优化(PSO)方法求解路径规划问题的改进优化技术。PSO是一种基于群体智能的随机优化技术,它模仿鱼群或鸟类群集的社会行为,用于定位移动机器人到达目标的最佳路径。使用MATLAB 2014编程语言进行的仿真结果证实,在相同的环境条件下,所提出的算法为移动机器人提供了最短的路径,优于标准版本的PSO算法。
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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24 weeks
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