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Active Learning of Probabilistic Movement Primitives

An active learning approach to learning a library of Probabilistic Movement Primitives capable of generalizing over a bounded space.

Learning Task Constraints from Demonstration for Hybrid Force/Position Control

We learn a dynamic constraint frame from demonstration for hybrid force/position control using Cartesian Dynamic Movement Primitives.