An Empirical Study for Fitness Function Selection in Fuzzy Logic Controllers for Mobile Robot Navigation

Author

Doitsidis, Lefteris ; Tsourveloudis, Nikos C.

Author_Institution

Dept. of Production Eng. & Manage., Tech. Univ. Crete

fYear

2006

fDate

6-10 Nov. 2006

Firstpage

3868

Lastpage

3873

Abstract

Fuzzy logic is widely used for mobile robot navigation. The main draw back of this approach is the ad hoc design of the controllers used. A popular method for the optimization of fuzzy logic controllers for the navigation of mobile robots is the use of genetic algorithms. An issue, in this procedure is the selection of the fitness function for the improvement of the behavior of a pre-designed controller. We analyze the factors that influence the evolution of the fuzzy controller based on the fitness function used and present some preliminary results. In order to validate our approach a test bed has been developed based in a low cost robot

Keywords

control system synthesis; fuzzy control; genetic algorithms; mobile robots; path planning; ad hoc design; fitness function selection; fuzzy logic controller design; genetic algorithms; mobile robot navigation; Control systems; Fuzzy control; Fuzzy logic; Genetic algorithms; Intelligent robots; Mobile robots; Navigation; Robot control; Robot sensing systems; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on

Conference_Location

Paris

ISSN

1553-572X

Print_ISBN

1-4244-0390-1

Type

conf

DOI

10.1109/IECON.2006.347417

Filename

4152914