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cs.RO2026
3PoinTr: 3D Point Tracks for Learning Manipulation from Unconstrained Human Videos
Adam Hung, Bardienus Pieter Duisterhof, Jeffrey Ichnowski
Learning manipulation policies from human videos could greatly reduce the need for expensive robot demonstrations, but existing approaches typically require restrictive assumptions…
cs.RO2025
MapExRL: Human-Inspired Indoor Exploration with Predicted Environment Context and Reinforcement Learning
Narek Harutyunyan, Brady Moon, Seungchan Kim +3
Path planning for robotic exploration is challenging, requiring reasoning over unknown spaces and anticipating future observations. Efficient exploration requires selecting budget-…
cs.RO2024
RoPotter: Toward Robotic Pottery and Deformable Object Manipulation with Structural Priors
Uksang Yoo, Adam Hung, Jonathan Francis +2
Humans are capable of continuously manipulating a wide variety of deformable objects into complex shapes. This is made possible by our intuitive understanding of material propertie…