RCT: A Robot-Collected Touch-Vision-Language Dataset for Tactile Generalization
For robots manipulating open-world objects, tactile representations must generalize to unseen materials. We introduce RCT (Robotic Contact Tactile), a robot-collected touch-vision-language dataset with 29,279 tactile frames from full robot presses on 122 industrial reference materials in 7 categories, recorded with three DIGIT sensors at multiple contact positions. RCT preserves each press as a contact sequence, enabling held-out evaluation across materials, categories, sensors, contact positions, and contact sequences. Frames from one press are strongly correlated: frame-random splits can pla
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- LinkedLinked via unknownVideo Friday: AI Gives Robot Hands Humanlike Dexterity →
- LinkedLinked via unknownVideo Friday: Give Robots a Hand →
- FuzzySimilar title/name (fuzzy) · 59%VioletVision-3B →
“Fuzzy title match (0.73): “RCT: A Robot-Collected Touch-Vision-Language Dataset for Tac” ≈ “VioletVision-3B””
- PossiblePossibly related (embedding) · 47%The 1X Neo Robot Has Freaky Fast Fingers →
- FuzzySimilar title/name (fuzzy) · 84%pytorch/vision →
“Fuzzy title match (0.92): “RCT: A Robot-Collected Touch-Vision-Language Dataset for Tac” ≈ “pytorch/vision””
- PossiblePossibly related (embedding) · 59%Grabette: an open system to record robot-manipulation data →
