Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot
Information SciencesPublished 8 March 2010
Oscar Castillo, Ricardo Martínez-Marroquín, Patricia Melín, Fevrier Valdez, José Soria
Citations272
SJR quartileQ1
SJR score1.80
SNIP1.98
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TL;DR
The application of Ant Colony Optimization and Particle Swarm Optimization on the optimization of the membership functions' parameters of a fuzzy logic controller in order to find the optimal intelligent controller for an autonomous wheeled mobile robot is described.
Abstract
In this paper we describe the application of Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) on the optimization of the membership functions' parameters of a fuzzy logic controller (FLC) in order to find the optimal intelligent controller for an autonomous wheeled mobile robot. The results obtained by the simulations performed are statistically compared among them and the previous work results obtained with GAs in order to find which is the best optimization technique for this particular robotics problem.
Keywords
Computer Science
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