Efficient and safe path planning for a mobile robot using genetic algorithm

Authors:
Mahmood Naderan-Tahan;Mohammad Taghi Manzuri-Shalmani
Affiliations:
Department of Computer Engineering, Sharif University of Technology, Tehran, Iran;Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

In this paper, a new method for path planning is proposed using a genetic algorithm (GA). Our method has two key advantages over existing GA methods. The first is a novel environment representation which allows a more efficient method for obstacles dilation in comparison to current cell based approaches that have a tradeoff between speed and accuracy. The second is the strategy we use to generate the initial population in order to speed up the convergence rate which is completely novel. Simulation results show that our method can find a near optimal path faster than computational geometry approaches and with more accuracy in smaller number of generations than GA methods.