1 citations · 3 across the 11 of their papers we have counts for
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EigenDEXplore: Structured Exploration for Dexterous Manipulation with Human Priors
Harsh Gupta, Tyler Ga Wei Lum, Changhao Wang +4
Dexterous manipulation poses a challenging high-dimensional optimization problem, as useful behaviors require coordinated motion across many hand joints. In reinforcement learning…
MessyMem: Learning-from-Doing Memory for Mobile Manipulation
Anuva Banwasi, William Muckelroy, Priya Sundaresan +3
Mobile manipulators deployed across many rooms and visits should improve with experience: after discovering that a cabinet is locked or finding an object in a drawer, the robot sho…
One Demonstration, Many Objects: Generalizing Manipulation via Local Contact Geometry
Satvik Sharma, Samrat Sahoo, Huang Huang +4
Dexterous manipulation with multi-fingered robot hands promises human-level dexterity, but collecting large-scale dexterous robot hand data remains difficult. Learning from human d…
Mixture of Frames Policy: Multi-Frame Action Denoising for Bimanual Mobile Manipulation
Dian Wang, Jisang Park, Xiaomeng Xu +3
Robotic manipulation is inherently multi-frame: local actions may be simple in an end-effector frame, while transport, upright-object handling, and whole-body coordination are bett…
CHORUS: Decentralized Multi-Embodiment Collaboration with One VLA Policy
Ria Doshi, Tian Gao, Annie Chen +2
Multi-robot collaboration allows robots to efficiently take on a wide range of tasks, from moving a couch through a doorway to assembling structures on a construction site. However…