A method to learn the inverse kinematics of multi-link robots by evolving neuro-controllers

Author:

H. José Antonio Martín,de Lope Javier,Santos Matilde

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference16 articles.

1. P.J. Alsina, N.S. Gehlot, Robot inverse kinematics: a modular neural network approach, in: Proceedings of 38th Midwest Symposium on Circuits and Systems, vol. 2, 1995, pp. 631–634.

2. An evolutionary algorithm that constructs recurrent neural networks;Angeline;IEEE Transactions on Neural Networks,1994

3. J. de Lope, T. Zarraonandia, R. González-Careaga, D. Maravall, Solving the inverse kinematics in humanoid robots: a neural approach, in: J. Mira, J.R. Álvarez (Eds.), Artificial Neural Nets Problem Solving Methods, vol. 2687, LNCS, Springer, Berlin, 2003, pp. 177–184.

4. A biomimetic approach for the stability of biped robots;de Lope,2005

5. J. de Lope Asiaín, R. González-Careaga, T. Zarraonandia, D. Maravall Gómez-Allende, Inverse kinematics for humanoid robots using artificial neural networks, in: R. Moreno-Díaz, F. Pichler (Eds.), Computer Aided Systems Theory—EUROCAST 2003, Revised Selected Papers, vol. 2809, LNCS, Springer, Berlin, 2003, pp. 448–459.

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