A Comparative Study of Optimization Algorithms for Global Path Planning of Mobile Robots

Authors : Mustafa Yusuf YILDIRIM, Rüştü AKAY

Pages : 417-428

Doi:10.16984/saufenbilder.800067

View : 25 | Download : 11

Publication Date : 2021-04-15

Article Type : Research Paper

Abstract :It is an essential issue for mobile robots to reach the target points with optimum cost which can be minimum duration or minimum fuel, depending on the problem. In this paper, it was aimed to develop a software for the optimal path planning of mobile robots in user-defined two-dimensional environments with static obstacles and to analyze the performance of some optimization algorithms for this problem using this software. The developed software is designed to create obstacles of different shapes and sizes in the work area and to find the shortest path for the robot using the selected optimization algorithm. Particle Swarm Optimization insert ignore into journalissuearticles values(PSO);, Artificial Bee Colony insert ignore into journalissuearticles values(ABC); and Genetic Algorithm insert ignore into journalissuearticles values(GA); were implemented in the software. These algorithms have been tested for optimum path planning in four models with different problem sizes and different difficulty levels. When the results are evaluated, it is observed that the ABC algorithm gives better results than other algorithms in terms of the shortest distance. With this study, the use of optimization algorithms in real-time path planning of land mobile robots or unmanned aerial vehicles can be simulated.
Keywords : mobile robot, path planning, cubic spline interpolation, optimization algorithms, simulation