By Topic

Integrated genetic algorithms and fuzzy control approach for optimization mobile robot navigation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Rekik, C. ; Sfax Eng. Sch., Univ. of Sfax, Sfax ; Jallouli, M. ; Derbel, N.

This paper presents an optimal fuzzy logic controller design using optimization techniques. The fuzzy logic controller (FLC) has been developed and implemented for the motion of the robot from an initial position towards another desired position, taking into account the kinematic constraints. First, we have carried out a simulation of a fuzzy logic based controller which determines the speed values of each driving wheel, while seeking the goal. Secondly, an optimization of this controller has been realized using gradient method and genetic algorithms. A comparison between these methods has been effected. Not only simulation results are shown in this paper, but the ldquoreal-timerdquo implementation has been realized onto the mini robot Khepera II. Simulation results verify successfully the application of the proposed method to real motion situations.

Published in:

Systems, Signals and Devices, 2009. SSD '09. 6th International Multi-Conference on

Date of Conference:

23-26 March 2009