Document Type : Review Article
Authors
Abstract
In this paper, a control strategy for a non-holonomic robot based on an Adaptive Neural Fuzzy Inference System is proposed. The neuro-controller makes it possible for the robot to track a given reference trajectory. After a short introduction about Adaptive Neural Fuzzy Inference System, the control strategy which is used on our virtual non-holonomic robot is described. And finally, the simulations’ results where the robot has to pass into a narrow path and also the first validation results concerning the implementation of the proposed concepts on a real robot is given.
Keywords
[1] Fukuda,T.; Nakagawa,S.; Kawauchi,Y. and Buss, M. (1998). "Self organizing robots based on cell structures – CEBOT". Proc IEEE Int. Workshop Intell. Robot. Syst., pp. 145–150.
[2] Parker, L. E. (2008). "Multiple Mobile Robot Systems". Springer Handbook of Robotics, pp: 921-941.
[3] Cao, Y.U.; Fukunaga, A.S.; Kahng, A.B. and Meng, F. (1997) "Cooperative mobile robotics: Antecedents and directions", Autonomous Robots, Vol 4, pp 1-23.
[4] Samson. C. (1995). "Control of chained systems application to the path following and time varying point-stabilization". IEEE Transactions on Automatic Control, vol 40.1, pp.64-77.
[5] Kolmanovsky, I. and McClamroch N.H. (1995). "Developments in nonholonomic control problems". IEEE Control Systems Magazine, Vol 15, pp.20-36.
[6] D’Andrea-Novel B.; Campion, G. and Bastin, G.(1995). "Control of nonholonomic wheeled mobile robots by state feedback linearization". The International Journal of Robotics Research, Vol. 14, No. 6, 543-559.
[7] De Luca, A. and Di Benedetto, M.D. ( 1993). "Control of noholonomic systems via dynamic compensation". Workshop on system structure and control N2, vol. 29, no 6, pp. 593-608.
[8] Fliess, M.; Levine, J. and Martin, P. (1995). "Flatness and defect of non-linear systems: introductory theory and examples". International Journal of Control, Vol. 61, No. 6, pp. 1327-1361.
[9] Morin, P. and Samon, C. (2003). "Practical stabilization of drift-less systems on Lie groups: the transverse function approach". IEEE Transactions on Automatic Control, vol. 48, no9, pp. 1496-1508.
[10] Barfoot, T.D. and Clark, C.M. (2004). "Motion Planning for Formations of Mobile Robots". Robotics and Autonomous Systems, Vol 46.2, pp.65-78.
[11] Jang, J.-S.R and Sun, C.T. (1995). " Neuro-fuzzy modeling and control" Proceedings of the IEEE, pp. 378-406.
[12] J. Godjevac (1995). "A Learning Procedure for a Fuzzy System: Application to Obstacle Avoidance". In Proceedings of the International Symposium on Fuzzy Logic, pp. 142-148
[13] Pascal, M. and Claude, S. (2008). "Motion Control of Wheeled Mobile Robots" Handbook of Robotics, S. Bruno, K.S Oussama (Eds), Springer-Verlag Berlin Heidelberg, pp.799-825.
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