Abstract
This paper presents an original method in the use of neural networks and backpropagation algorithm to learn control of robotics systems. The originality consists to express the control objective as a criterion of which the gradient is backpropagating through the network instead of the classical quadratic error used in standard backpropagation. This technic allows on-line learning that is impossible to do with standard backpropagation. Experimental validation is realised by the position and the orientation control of a faster industrial mobile robot. Results show the feasability of the method, and particularly establish that on-line learning scheme permit to refine the weights of the network in front of the kinematics constraints of the robot.
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References
D.E Rummelhart, J.L. McClelland, “Parallel Distributed Processing”, MIT Press, pp. 318–362, 1986
A. Guez, J. Selinsky, A neuromorphic controller with a human teacher, Proc. of IEEE International Conference on Neural Networks, pp 595–602, 1988
D. Nguyen, B. Widrow “Neural Networks for Self-Learning Control Systems”,IEEE Work. on Industrial Applications of Neural Networks, pp 18–23, 1991
S. Delaplace, “Navigation d Coût Minimal d’un Robot Mobile dans un Environnement Partiellement Connu”’ thèse de l’Université Paris 6 ( Pierre et Marie Curie ), France, November 1991
D.M.A. Lee, W.H. ElMaraghy, “A Neural Network Solution for Biped Gait Synthesis”, Int. Joint Conf. on Neural Networks, Vol II, pp. 763–767, 1992
M.I. Jordan and D.E Rummelhart, “Forwars Models: Supervised Learning with a Distal Teacher”, Cognitive Science, Vol 16, pp. 307–354, 1992
C. K. Ait-Abderrahim, “Commande de Robots Mobiles”, Thèse de l’Ecole des Mines de Paris, 1993.
P. Hénaff, H. Schwenk,M. Milgram “ A Neural Network Approach of the Control of Dynamic Biped Equilibrium”,International Symposium on Measurement and Control in Robotics,1993
P. Hénaff, “Mises en Œuvre de Commandes Neuronales par Rétropropagation Indirecte: Application d la Robotique Mobile”, thèse de l’Université Paris 6 ( Pierre et Marie Curie ), France, june 1994
P. Hénaff, “Adaptive Neural Control In mobile Robotics: Experimentation for a Wheeled Cart”, IEEE Int. Conf. on Systems, Man and Cybernetics, pp 1139–1144, Oct. 1994
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© 1997 Springer-Verlag Wien
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Henaff, P., Delaplace, S. (1997). Using Backpropagation Algorithm for Neural Adaptive Control: Experimental Validation on an Industrial Mobile Robot. In: Morecki, A., Bianchi, G., Rzymkowski, C. (eds) ROMANSY 11. International Centre for Mechanical Sciences, vol 381. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2666-0_40
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DOI: https://doi.org/10.1007/978-3-7091-2666-0_40
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82903-5
Online ISBN: 978-3-7091-2666-0
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