Abstract
This paper deals with the methodological approach for the development and implementation of force-position control for robotized systems. We propose a first approach based on neural network to treat globally the problem of the adaptation of robot behavior to various classes of tasks and to actual conditions of the task where its parameters may vary. The obtained results are presented and analyzed in order to prove the efficiency of the proposed approach
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© 2001 Springer-Verlag Berlin Heidelberg
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Saadia, N., Amirat, Y., Pontnaut, J., Ramdane-Cherif, A. (2001). Neural Adaptive Force Control for Compliant Robots. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_52
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DOI: https://doi.org/10.1007/3-540-45723-2_52
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