Dexterous manipulation involves not only moving objects, but also arranging the hand around them to maintain useful contacts and enable subsequent actions. Yet many learning-based systems specify goals primarily through object poses or trajectories, leaving hand-object configurations to emerge implicitly. We introduce...
Zhe-Wei Gui, Anthony Bolton, Ji-Yao Zhang et al.· 0 citations
Category-level in-hand manipulation of articulated objects is a formidable yet underexplored challenge for dexterous robotic hands. This difficulty stems from two core bottlenecks: first, controlling an object's internal degrees of freedom is tightly coupled with maintaining grasp stability on a free-floating base; sec...
Yang Yang, Teng-Yu Liu, Pu-Hao Li et al.· 1 citation
TeleDexter is introduced, a hand-object co-tracking controller that maps operator intent into learned, low-level contact execution that successfully train autonomous policies via behavioral cloning, marking a concrete step towards human-level dexterous teleoperation.
