Natural Inspiration for Artificial Adaptivity: Some Neurocomputing Experiences in Robotics

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Conference object , Article 01 Jan 2005Publisher:Springer Berlin Heidelberg

Authors: Carme Torras;

doi: 10.1007/11560319_5

handle: 10261/30300

Natural Inspiration for Artificial Adaptivity: Some Neurocomputing Experiences in Robotics

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Abstract

The biological world offers a full range of adaptive mechanisms, from which technology researchers try to get inspiration. Among the several disciplines attempting to reproduce these mechanisms artificially, this paper concentrates on the field of Neural Networks and its contributions to attain sensorimotor adaptivity in robots. Essentially this type of adaptivity requires tuning nonlinear mappings on the basis of input-output information. Several experimental robotic systems are described, which rely on inverse kinematics and visuomotor mappings. Finally, the main trends in the evolution of neural computing are highlighted, followed by some remarks drawn from the surveyed applications.

International Conference on Unconventional Models of Computation (UC), 2005, Sevilla (España)

This work was supported by the project 'Grup de recerca consolidat - ROBÒTICA' (8007).

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Cybernetics

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