VitaTouch combines vision-tactile encoders with a dual Q-Former and contrastive alignment to an LLM, achieving 88.89% hardness and 75.13% roughness accuracy on a new 186-object dataset plus 94% success in robotic sorting trials.
Deep learning-assisted real-time defect detection and closed-loop adjustment for additive man- ufacturing of continuous fiber-reinforced polymer composites
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VitaTouch: Property-Aware Vision-Tactile-Language Model for Robotic Quality Inspection in Manufacturing
VitaTouch combines vision-tactile encoders with a dual Q-Former and contrastive alignment to an LLM, achieving 88.89% hardness and 75.13% roughness accuracy on a new 186-object dataset plus 94% success in robotic sorting trials.