Adaptive Neuro-Fuzzy Controler With Genetic Training For Mobile Robot Control

Authors

  • Olumide Obe "Politehnica" University of Bucharest, Romania
  • Ioan Dumitrache "Politehnica" University of Bucharest, Romania

Keywords:

Khepera, fuzzy controller, neuro-fuzzy controller, navigation, genetic algorithm

Abstract

In this paper, we investigate the use of adaptive techniques in the optimization of navigation of Khepera mobile robot in an unstructured and dynamic environment. We optimize the performance of our simplified fuzzy controller using neural network that utilizes genetic algorithm learning. The adaptation of the system involves the tuning of the control rules thereby trimming the control actions, and adjusting the fuzzy controller output gain. We realised an improved performance in our adaptive neuro-fuzzy controller with genetic training for various implemented behaviours on the robot.

References

I. Dumitrache, 1996, Intelligent Control of industrial Robots, Mediamira Press, Cluj, 1996.

I. Dumitrache, 2000, Intelligent Autonomous Systems, Revue Roumaine des Sciences techiniques - Electrotechique et Energetique, Vol. 45, No.3, Pp. 439-453, Bucharest.

R.R. Murphy, 2000, Introduction to AI Robotics,MIT Press.

I. Dumitrache and M. Dragocea, 2006, Some problems of advanced mobile robot control, EAI, Vol. 7, No. 4, pp. 11-30

G. Campion, G. Bastin, 1996, Structural Properties and classification of Kinematics and ynamic Model of wheeled Mobile Robots, IEEE Transaction on Robotics and Automation, ol. 12,No. 1.

H.R. Everett, 1995, Sensors for Mobile Robots,A.K. Peters, Ltd.

X.Q. Chen, Y.Q. Chen, and J.G. Chase, Mobiles Robots-Past Present and Future, Intech.

R. A. Brooks, 1986, A robust layered control system for a mobile robot. IEEE Journal of obotics and Automation, RA-2(1):14-23.

R. A. Brooks, 1999, Cambrian Intelligence: The Early History of the New AI, The MIT ress, Cambridge, Massachusetts.

L.A. Zadeh, 1994, Fuzzy logic, Neural networks, and soft computing, Communications of he ACM, 37(3):77-84.

O.O.Obe and I. Dumitrache, Fuzzy Control of Autonomous Mobile Robot, U.P.B. Sci. Bull., eries C, Vol. 72,Iss. 3, 2010

M.Jackson Phinni et al, Obstacle Avoidance of a wheel mobile Robot: A Genetic-neurofuzzy pproach, IISc Centary-International Conference on Advances in Mechanical Engineering (IC-ICAME),Bangalore, India, July, 2008

Published

2012-03-01

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