Learning and generation of goal-directed arm reaching from scratch

Neural Networks : the Official Journal of the International Neural Network Society
Hiroyuki KambaraYasuharu Koike

Abstract

In this paper, we propose a computational model for arm reaching control and learning. Our model describes not only the mechanism of motor control but also that of learning. Although several motor control models have been proposed to explain the control mechanism underlying well-trained arm reaching movements, it has not been fully considered how the central nervous system (CNS) learns to control our body. One of the great abilities of the CNS is that it can learn by itself how to control our body to execute required tasks. Our model is designed to improve the performance of control in a trial-and-error manner which is commonly seen in human's motor skill learning. In this paper, we focus on a reaching task in the sagittal plane and show that our model can learn and generate accurate reaching toward various target points without prior knowledge of arm dynamics. Furthermore, by comparing the movement trajectories with those made by human subjects, we show that our model can reproduce human-like reaching motions without specifying desired trajectories.

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Citations

Aug 31, 2013·Biological cybernetics·Satoshi ItoDavid J Ostry
Jan 18, 2013·Journal of Neurophysiology·Hiroyuki KambaraYasuharu Koike
Jan 31, 2018·Neural Computation·Kyuengbo MinHideyuki Kimpara
May 30, 2014·International Journal of Rehabilitation Research. Internationale Zeitschrift Für Rehabilitationsforschung. Revue Internationale De Recherches De Réadaptation·Matjaž Zadravec, Zlatko Matjačić
May 7, 2020·Frontiers in Bioengineering and Biotechnology·Katrin StollenmaierDaniel F B Haeufle
Jan 31, 2018·Frontiers in Human Neuroscience·Luka PeternelJan Babič
Jan 12, 2021·Frontiers in Computational Neuroscience·Kyuengbo MinShinji Kakei
Mar 20, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Hiroyuki KambaraYasuharu Koike
Aug 26, 2014·The Journal of Experimental Biology·Yusuke Tomina, Masakazu Takahata

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