TacSushi: Tactile-Grounded World-Action Modeling for Dexterous Sushi Manipulation
Dexterous food manipulation requires control under deformation, occlusion, and uncertain contact. We present TacSushi, a tactile-grounded, Cosmos3-based world-action policy that learns from recorded future consequences while acting on current observations. The backbone encodes current RGB, language, and hand state, and feature-wise gated fusion incorporates fingertip tactile features into the action representation. During training, a decoder conditioned on demonstrated action chunks predicts logged future visual observations, task progress, relative contact risk, and tactile summaries; this decoder is removed at deployment. Failed trials provide consequence supervision, but their actions ...
| Authors | Haodi Hu, Kaen Kogashi, Toshiaki Koike-Akino |
|---|---|
| Primary category | cs.RO |
| Published | 17 September 2026 |
| Last updated at source | 24 September 2026 |
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