ROJun 3

TransTac: Visuo-Tactile Modality Transition via Ultraviolet-Encoded Transparent Elastomers

arXiv:2606.0447752.5
AI Analysis

For robotics and tactile sensing, this work enables simultaneous visual and tactile perception through a single transparent sensor, overcoming the opacity limitation of existing vision-based tactile sensors.

TransTac introduces a transparent UV-encoded visuo-tactile sensor that combines vision and tactile sensing in one device, achieving 83.3% zero-shot tactile recognition accuracy (≈50 pp improvement over opaque baselines) and 21% better stereo matching robustness.

Vision-based tactile sensors (VBTS) recover high-resolution contact geometry but typically rely on opaque elastomer layers that prevent visual transparency, while RGB-D cameras provide global depth perception yet degrade significantly at close range. To address this limitation, we present TransTac, a transparent ultraviolet (UV)-encoded binocular VBTS that integrates visual observation and marker-based tactile reconstruction within a single compact device. The system employs a transparent elastomer embedded with UV-reflective markers and a prior-guided Delaunay stereo matching algorithm for robust sparse triangulation. To reliably detect densely distributed semitransparent markers, we develop a lightweight detector that enables stable localization under contact and deformation. The proposed prior-guided Delaunay matching improves correspondence robustness by approximately 21% compared with global assignment baselines while maintaining high reconstruction accuracy. In semantic evaluation, TransTac achieves up to 83.3% zero-shot recognition accuracy on tactile images, exceeding opaque tactile baselines by approximately 50 percentage points. Embedding analysis further reveals substantially stronger cross-modal alignment with natural images, with class-center similarity increasing from around 0.2 to over 0.77. Controlled near-distance experiments quantify the degradation of RGB-D depth reliability and demonstrate extended geometric coverage enabled by visuo-tactile integration. Finally, a compact prototype is implemented with an approximate hardware cost of $70.

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