Automatic design of fuzzy logic controller using a genetic algorithm for collision-free, time-optimal navigation of a car-like robot

Article type: Research Article

Authors: Hui, Nirmal Baran | Pratihar, Dilip Kumar^{; *}

Affiliations: Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur-721 302, India

Correspondence: [*] Corresponding author. Tel.: +91 3222 282992; Fax: +91 3222 282278; E-mail: [email protected]

Abstract: A fuzzy logic controller (FLC), intended to plan and control the motion of a car-like robot during its navigation among several moving obstacles, is designed automatically using a genetic algorithm (GA). The FLC is expressed by utilizing the structure of a neural network (NN), and a GA is used to optimize both its data base as well as rule base. An importance factor is introduced to determine the strength of a rule and thus justify its redundancy, if any. Results of the proposed approach are compared to those of a neuro-fuzzy approach, genetic-neuro-fuzzy approach and a potential field method, through computer simulations, for solving the navigation problems of a car-like robot. The present approach is found to perform better than the other three approaches, for most randomly-generated test scenarios.

Keywords: Fuzzy logic control, automatic design, genetic algorithm, car-like robot, navigation

DOI: 10.3233/HIS-2005-2301

Journal: International Journal of Hybrid Intelligent Systems, vol. 2, no. 3, pp. 161-187, 2005