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dc.contributor.author Hiratsuka, M
dc.contributor.author Makondo, N
dc.contributor.author Rosman, Benjamin S
dc.contributor.author Hasegawa, O
dc.date.accessioned 2017-02-23T09:39:28Z
dc.date.available 2017-02-23T09:39:28Z
dc.date.issued 2016-10
dc.identifier.citation Hiratsuka, M., Makondo, N., Rosman, B.S. and Hasegawa, O. 2016. Trajectory learning from human demonstrations via manifold mapping. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 9-14 October 2016, Daejeon Convention Center, Daejeon, Korea en_US
dc.identifier.uri http://ieeexplore.ieee.org/document/7759579/
dc.identifier.uri http://hdl.handle.net/10204/8935
dc.description 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 9-14 October 2016, Daejeon Convention Center, Daejeon, Korea en_US
dc.description.abstract This work proposes a framework that enables arbitrary robots with unknown kinematics models to imitate human demonstrations to acquire a skill, and reproduce it in real-time. The diversity of robots active in non-laboratory environments is growing constantly, and to this end we present an approach for users to be able to easily teach a skill to a robot with any body configuration. Our proposed method requires a motion trajectory obtained from human demonstrations via a Kinect sensor, which is then projected onto a corresponding human skeleton model. The kinematics mapping between the robot and the human model is learned by employing Local Procrustes Analysis, which enables the transfer of the demonstrated trajectory from the human model to the robot. Finally, the transferred trajectory is modeled using Dynamic Movement Primitives, allowing it to be reproduced in real time. Experiments in simulation on a 4 degree of freedom robot show that our method is able to correctly imitate various skills demonstrated by a human. en_US
dc.language.iso en en_US
dc.publisher IEEE Xplore en_US
dc.relation.ispartofseries Wokflow;17894
dc.subject Demonstration learning en_US
dc.subject Manifold mapping en_US
dc.subject Skills transfer en_US
dc.title Trajectory learning from human demonstrations via manifold mapping en_US
dc.type Presentation en_US


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