Balancing Marker and Markerless Modes in Vision-Based Tactile Sensors with a Translucent Skin

Abstract

Vision-based tactile sensors (VBTS) face an inherent trade-off in tactile skin design. Opaque ink markers enable accurate force and tangential displacement estimation but occlude geometric features essential for object and texture classification. Conversely, markerless skins preserve surface details yet provide limited capability for tangential motion estimation. Existing approaches, including UV illumination and learning-based virtual marker transfer, increase hardware complexity or computational cost. We present a novel tactile skin with translucent, tinted markers balancing the modes of marker and markerless for VBTS. This design enables concurrent tangential displacement tracking, force estimation, and preservation of surface geometry. It integrates directly with the GelSight sensor family, requiring no additional hardware and minimal software modification. Experimental evaluation demonstrates that translucent skin improves overall sensing performance relative to both opaque-marker and markerless configurations. It achieves 99.17% accuracy in object classification, 93.51% in texture classification, 97% point retention in tangential displacement tracking, and a 66% reduction in total force error. These results indicate that translucent skin substantially mitigate the traditional trade-off between marker-based and markerless tactile sensing, thereby expanding the applicability of multi-modal VBTS in tactile robotics.