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Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation
Real-world robotic assembly at sub-millimeter tolerances demands spatial precision, compliant interaction, and robustness to contact failures. We present Facet-0, a robotic foundation model that predicts and values the contact consequences of its actions. Facet-0 unifies multimodal representation learning and reinforcement learning (RL) post-training around a joint action-wrench proposal: a causal wrench history is aligned with vision-language semantics and kinematic state, and flow matching generates each action chunk together with the future wrist-wrench profile it is expected to induce. Dep
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T17:58:07.000Z
First collected: 2026-09-21T06:01:56.170Z. This is not the publication date.