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cs.RO2024
Investigating the Benefits of Nonlinear Action Maps in Data-Driven Teleoperation
Michael Przystupa, Gauthier Gidel, Matthew E. Taylor +3
As robots become more common for both able-bodied individuals and those living with a disability, it is increasingly important that lay people be able to drive multi-degree-of-free…
cs.RO2024
Deep Probabilistic Movement Primitives with a Bayesian Aggregator
Michael Przystupa, Faezeh Haghverd, Martin Jagersand +1
Movement primitives are trainable parametric models that reproduce robotic movements starting from a limited set of demonstrations. Previous works proposed simple linear models tha…