Skill learning based catching motion control

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dc.contributor.author Cimen, Goekcen
dc.contributor.author Kavafoglu, Zumra
dc.contributor.author Kavafoglu, Ersan
dc.contributor.author Capin, Tolga
dc.contributor.author Gurcay, Hasmet
dc.date.accessioned 2019-06-25T14:33:31Z
dc.date.available 2019-06-25T14:33:31Z
dc.date.issued 2015
dc.identifier.issn 1546-4261
dc.identifier.issn 1546-427X
dc.identifier.uri https://doi.org/10.1002/cav.1659
dc.identifier.uri https://acikerisim.tedu.edu.tr/xmlui/handle/20.500.12485/143
dc.description.abstract Learned biomechanical strategies prepare the human body in kinematics and kinetics terms during interception tasks, such as throwing and catching, in real world. Based on this, we present a real-time physics-based approach that generates natural and physically plausible motions for a highly complex task ball catching. We showed that ball catching behavior could be achieved with the proper combination of rather simple motor skills, such as standing, walking, and reaching. The character learns some policies to know how and when to react by using reinforcement learning in order to use time accurately. We demonstrate the effectiveness of our method with some of the catching animation results in different catching strategies. Copyright (c) 2015John Wiley & Sons, Ltd. en_US
dc.language.iso en en_US
dc.publisher WILEY-BLACKWELL, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA en_US
dc.subject Computer Science en_US
dc.title Skill learning based catching motion control en_US
dc.type Article en_US
dc.relation.journal Computer Animation and Virtual Worlds
dc.identifier.issue 3-4
dc.identifier.startpage 217
dc.identifier.endpage 225
dc.identifier.volume 26

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