Tube Diffusion Policy learns observation-conditioned feedback flows around nominal action chunks to enable fast reactive control in visual-tactile contact-rich manipulation.
Interpolated adaptive linear reduced order modeling for deformation dynamics
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Contact-Grounded Policy predicts coupled robot-state and tactile trajectories with a diffusion model and maps them via a learned consistency function to executable targets for compliance controllers, outperforming standard visuotactile diffusion baselines on physical and simulated dexterous tasks.
citing papers explorer
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Tube Diffusion Policy: Reactive Visual-Tactile Policy Learning for Contact-rich Manipulation
Tube Diffusion Policy learns observation-conditioned feedback flows around nominal action chunks to enable fast reactive control in visual-tactile contact-rich manipulation.
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Contact-Grounded Policy: Dexterous Visuotactile Policy with Generative Contact Grounding
Contact-Grounded Policy predicts coupled robot-state and tactile trajectories with a diffusion model and maps them via a learned consistency function to executable targets for compliance controllers, outperforming standard visuotactile diffusion baselines on physical and simulated dexterous tasks.