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Authors: Claudia Casellato 1 ; Jesus A. Garrido 2 ; Cristina Franchin 1 ; Giancarlo Ferrigno 1 ; Egidio D'Angelo 3 and Alessandra Pedrocchi 1

Affiliations: 1 Politecnico di Milano, Italy ; 2 University of Pavia and Consorzio Interuniversitario per le Scienze Fisiche della Materia (CNISM), Italy ; 3 University of Pavia, IRCCS, Istituto Neurologico Nazionale C. Mondino and Brain Connectivity Center, Italy

Keyword(s): Cerebellum, Learning, Vestibular-Ocular Reflex, Plasticity.

Abstract: Biologically inspired neural mechanisms, coupling internal models and adaptive modules, can be an effective way of constructing a control system that exhibits a human-like behaviour. A brain-inspired controller has been developed, embedding a cerebellum-like adaptive module based on neurophysiological plasticity mechanisms. It has been tested as controller of an ad-hoc developed neurorobot, integrating a 3 degrees of freedom serial robotic arm with a motion tracking system. The learning skills have been tried out, designing a vestibular-ocular reflex (VOR) protocol. One robot joint was used to get the desired head turn, while another joint displacement corresponded to the eye motion, which was controlled by the cerebellar model output, used as joint torque. Along task repetitions, the cerebellum was able to produce an anticipatory eye displacement, which accurately compensated the head turn in order to keep on fixing the environmental object. Multiple tests have been implemented, pai ring different head turn with object motion. The gaze error and the cerebellum output were quantified. The VOR was accurately tuned thanks to the cerebellum plasticity. The next steps will include the activation of multiple plasticity sites evaluating the real platform behaviour in different sensorimotor tasks. (More)

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Paper citation in several formats:
Casellato, C.; A. Garrido, J.; Franchin, C.; Ferrigno, G.; D'Angelo, E. and Pedrocchi, A. (2013). Brain-inspired Sensorimotor Robotic Platform - Learning in Cerebellum-driven Movement Tasks through a Cerebellar Realistic Model. In Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - SSCN; ISBN 978-989-8565-77-8; ISSN 2184-3236, SciTePress, pages 568-573. DOI: 10.5220/0004659305680573

@conference{sscn13,
author={Claudia Casellato. and Jesus {A. Garrido}. and Cristina Franchin. and Giancarlo Ferrigno. and Egidio D'Angelo. and Alessandra Pedrocchi.},
title={Brain-inspired Sensorimotor Robotic Platform - Learning in Cerebellum-driven Movement Tasks through a Cerebellar Realistic Model},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - SSCN},
year={2013},
pages={568-573},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004659305680573},
isbn={978-989-8565-77-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - SSCN
TI - Brain-inspired Sensorimotor Robotic Platform - Learning in Cerebellum-driven Movement Tasks through a Cerebellar Realistic Model
SN - 978-989-8565-77-8
IS - 2184-3236
AU - Casellato, C.
AU - A. Garrido, J.
AU - Franchin, C.
AU - Ferrigno, G.
AU - D'Angelo, E.
AU - Pedrocchi, A.
PY - 2013
SP - 568
EP - 573
DO - 10.5220/0004659305680573
PB - SciTePress