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Anticipatory grip force control using a cerebellar model

de Gruijl, J.R. und van der Smagt, Patrick und De Zeeuw, C.I. (2009) Anticipatory grip force control using a cerebellar model. Neuroscience, 162 (3), Seiten 777-786. Elsevier Ltd.. DOI: 10.1016.

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Offizielle URL: http://dx.doi.org/10.1016/j.neuroscience.2009.02.041

Kurzfassung

Grip force modulation has a rich history of research, but the results remain to be integrated as a neurocomputational model and applied in a robotic system. Adaptive grip force control as exhibited by humans would enable robots to handle objects with sufficient yet minimal force, thus minimizing the risk of crushing objects or inadvertently dropping them. We investigated the feasibility of grip force control by means of a biological neural approach to ascertain the possibilities for future application in robotics. As the cerebellum appears crucial for adequate grip force control, we tested a computational model of the olivo-cerebellar system. This model takes into account that the processing of sensory signals introduces a 100 ms delay, and because of this delay, the system needs to learn anticipatory rather than feedback control. For training, we considered three scenarios for feedback information: (1) grip force error estimation, (2) sensory input on deformation of the fingertips, and (3) as a control, noise. The system was trained on a data set consisting of force and acceleration recordings from human test subjects. Our results show that the cerebellar model is capable of learning and performing anticipatory grip force control closely resembling that of human test subjects despite the delay. The system performs best if the delayed feedback signal carries an error estimation, but it can also perform well when sensory data are used instead. Thus, these tests indicate that a cerebellar neural network can indeed serve well in anticipatory grip force control not only in a biological but also in an artificial system.

Dokumentart:Zeitschriftenbeitrag
Titel:Anticipatory grip force control using a cerebellar model
Autoren:
AutorenInstitution oder E-Mail-Adresse der Autoren
de Gruijl, J.R.Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam
van der Smagt, PatrickNICHT SPEZIFIZIERT
De Zeeuw, C.I.Department of Neuroscience, Erasmus MC, Rotterdam
Datum:26 Februar 2009
Erschienen in:Neuroscience
Referierte Publikation:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:162
DOI :10.1016
Seitenbereich:Seiten 777-786
Verlag:Elsevier Ltd.
Name der Reihe:New Insights in Cerebellar Function
Status:veröffentlicht
Stichwörter:cerebellum; grip force; motor learning; computational model
HGF - Forschungsbereich:Verkehr und Weltraum (alt)
HGF - Programm:Weltraum (alt)
HGF - Programmthema:W SY - Technik für Raumfahrtsysteme
DLR - Schwerpunkt:Weltraum
DLR - Forschungsgebiet:W SY - Technik für Raumfahrtsysteme
DLR - Teilgebiet (Projekt, Vorhaben):W - Weiterentwicklung Robotik - Mechatronik und Dynamik (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Robotik und Mechatronik > Robotersysteme
Hinterlegt von: Gabriele Beinhofer
Hinterlegt am:13 Jan 2010 13:20
Letzte Änderung:12 Dez 2013 20:51

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