SO-TA replaces standard attention with optimal-transport alignment across vision, force/torque, and proprioception to improve diffusion-policy performance on real-robot insertion and wiping tasks.
A survey of robot learning from demonstration
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.RO 2years
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UNVERDICTED 2representative citing papers
A VR gamified data collection system in Unity for humanoid robots demonstrates broad state-action coverage in pick-and-place tasks, with higher difficulty increasing motion intensity and workspace exploration.
citing papers explorer
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Spacetime Optimal-Transport Attention for Visuo-Haptic Imitation Learning of Contact-Rich Manipulation
SO-TA replaces standard attention with optimal-transport alignment across vision, force/torque, and proprioception to improve diffusion-policy performance on real-robot insertion and wiping tasks.
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Leveraging VR Robot Games to Facilitate Data Collection for Embodied Intelligence Tasks
A VR gamified data collection system in Unity for humanoid robots demonstrates broad state-action coverage in pick-and-place tasks, with higher difficulty increasing motion intensity and workspace exploration.