2 papers
cs.LG2025
Efficient Morphology-Aware Policy Transfer to New Embodiments
Michael Przystupa, Hongyao Tang, Martin Jagersand +4
Morphology-aware policy learning is a means of enhancing policy sample efficiency by aggregating data from multiple agents. These types of policies have previously been shown to he…
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…