Human movement learning with dynamic movement primitives combined with mixture models

dc.contributor.author	Alizadeh, T.
dc.contributor.author	Calinon, S.
dc.date.accessioned	2015-10-22T11:30:36Z
dc.date.available	2015-10-22T11:30:36Z
dc.date.issued	2014
dc.identifier.uri	http://nur.nu.edu.kz/handle/123456789/422
dc.description.abstract	The proposed research is to provide a probabilistic approach to learn human movements. Dynamical Movement Primitives (DMP) have been extensively used in robotics in order to learn human motions [1]. The DMP modulates a virtual spring with a learned non-linear force profile /(x), perturbing the system to make it follow a desired trajectory.	ru_RU
dc.language.iso	en	ru_RU
dc.publisher	Nazarbayev University	ru_RU
dc.subject	dynamical movement primitives	ru_RU
dc.subject	human motions	ru_RU
dc.subject	mixture models	ru_RU
dc.title	Human movement learning with dynamic movement primitives combined with mixture models	ru_RU
dc.type	Abstract	ru_RU