Skill learning based catching motion control

buir.advisorÇapın, Tolga
dc.contributor.authorÇimen, Gökçen
dc.date.accessioned2016-01-08T20:18:25Z
dc.date.available2016-01-08T20:18:25Z
dc.date.issued2014
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionAnkara : The Department of Computer Engineering and The Graduate School of Engineering and Science of Bilkent Univesity, 2014.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2014.en_US
dc.descriptionIncludes bibliographical references leaves 55-59.en_US
dc.description.abstractIn real world, it is crucial to learn biomechanical strategies that prepare the body in kinematics and kinetics terms during the interception tasks, such as kicking, throwing and catching. Based on this, we presents a real-time physics-based approach that generate natural and physically plausible motions for a highly complex task- ball catching. We showed that ball catching behavior as many other complex tasks, can be achieved with the proper combination of rather simple motor skills, such as standing, walking, reaching. Since learned biomechanical strategies can increase the conscious in motor control, we concerned several issues that needs to be planned. Among them, we intensively focus on the concept of timing. 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 by presenting some of the catching animation results executed in different catching strategies.In each simulation, the balls were projected randomly, but within a interval of limits, in order to obtain different arrival flight time and height conditions.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityÇimen, Gökçenen_US
dc.embargo.release2016-07-23
dc.format.extentxii, 59 leaves, graphics, illustrationsen_US
dc.identifier.itemidB147667
dc.identifier.urihttp://hdl.handle.net/11693/18340
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBall Catching Simulationen_US
dc.subjectPhysics-Based Character Animationen_US
dc.subjectRein-forcement Learningen_US
dc.subject.lccTA1634 .C56 2014en_US
dc.subject.lcshHuman mechanics--Research.en_US
dc.subject.lcshMotion--Computer simulation.en_US
dc.subject.lcshComputer animation.en_US
dc.subject.lcshBiomechanics.en_US
dc.titleSkill learning based catching motion controlen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
thesis.pdf
Size:
7.5 MB
Format:
Adobe Portable Document Format
Description:
Full printable version