Publication Details

SELECT * FROM publications WHERE Record_Number=11388
Reference TypeConference Proceedings
Author(s)Urain, J.; Tateo, D.; Ren, T.; Peters, J.
TitleStructured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems
Journal/Conference/Book TitleNeurIPS 2020, 3rd Robot Learning Workshop
KeywordsMovement Primitives, Imitation Learning, Inductive Bias
AbstractWe present a new family of deep neural network-based dynamic systems. The presented dynamics are globally stable and can be conditioned with an arbitrary context state. We show how these dynamics can be used as structured robot policies. Global stability is one of the most important and straightforward inductive biases as it allows us to impose reasonable behaviors outside the region of the demonstrations.
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