arXiv AI By Jingbo He, Michael F\"arber, Roberto Calandra

RCT: A Robot-Collected Touch-Vision-Language Dataset for Tactile Generalization

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arXiv:2606. 31694v1 Announce Type: cross Abstract: For robots manipulating open-world objects, tactile representations must generalize to unseen materials.

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TacCoRL: Integrating Tactile Feedback into VLA via Simulation

arXiv:2606. 11743v1 Announce Type: cross Abstract: Vision-language-action (VLA) models provide strong visual, language, and action priors for robot manipulation, but visual observations alone often miss the local contact state required for contact-rich tasks.

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OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies

arXiv:2607. 03723v1 Announce Type: cross Abstract: Visual policies learned from human videos, teleoperation, and robot demonstrations offer scalable motion priors, but often fail in contact-rich manipulation, where success significantly depends on local force and contact geometry.

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