Path planning of mobile robot with neuro-genetic-fuzzy technique in static environment

Authors:
Thongam Khelchandra;Jie Huang;Somen Debnath
Affiliations:
Information Systems Department, The University of Aizu, Aizu-Wakamatsu, Japan;Information Systems Department, The University of Aizu, Aizu-Wakamatsu, Japan;Department of Information Technology, Mizoram University, Tanhril, Aizawl, India
Venue:
International Journal of Hybrid Intelligent Systems
Year:
2014

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Abstract

This paper presents a technique of path planning of a mobile robot using artificial neural network, fuzzy logic and genetic algorithm. The artificial neural network ANN is trained to choose a path from a set of n paths for the mobile robot to move ahead towards the destination. Fuzzy logic FL is used to avoid collisions when all the n paths are blocked by obstacles. Genetic Algorithm GA is used as optimizer to find optimal locations along the obstacle-free directions and positions by selecting a set of fuzzy rules for the fuzzy logic system from a large rule base. Results show that the combination of these features is computationally efficient by helping each other to eliminate their individual limitations.