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

Abstract

From the time being, there are even instances for application of mobile robots in our life
like in home, schools, hospitals, etc. The goal of this paper is to plan a path and minimizing the
path lengths with obstacles avoidance for a mobile robot in static environment. In this work we
depict the issue of off-line wheeled mobile robot (WMR) path planning, which best route for
wheeled mobile robot from a start point to a target at a plane environment represented by 2-D
work space. A modified optimization technique to solve the problem of path planning problem
using particle swarm optimization (PSO) method is given. PSO is a swarm intelligence based
stochastic optimization technique which imitate the social behavior of fish schooling or bird
flocking, 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, confirmed
that the suggested algorithm outperforms the standard version of PSO algorithm with the same
environment conditions by providing the shortest path for mobile robot.