Mixture of Attractors: A Novel Movement Primitive Representation for Learning 
Motor Skills From Demonstrations

Manschitz, S.; Gienger, M.; Kober, J.; Peters, J

doi:10.1109/LRA.2018.2792531

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Mixture of Attractors: A Novel Movement Primitive Representation for Learning Motor Skills From Demonstrations

MPS-Authors

/persons/resource/persons84135

Peters, J
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Manschitz, S., Gienger, M., Kober, J., & Peters, J. (2018). Mixture of Attractors: A Novel Movement Primitive Representation for Learning Motor Skills From Demonstrations. IEEE Robotics and Automation Letters, 3(2), 926-933. doi:10.1109/LRA.2018.2792531.

Cite as: https://hdl.handle.net/21.11116/0000-0003-781A-A

Abstract

There is no abstract available