Monocular Reconstruction of Neural Tactile Fields

• URL: http://arxiv.org/abs/2602.12508v1
• Date: Fri, 13 Feb 2026 01:25:19 GMT
• Title: Monocular Reconstruction of Neural Tactile Fields
• Authors: Pavan Mantripragada, Siddhanth Deshmukh, Eadom Dessalene, Manas Desai, Yiannis Aloimonos,
• Abstract summary: We introduce neural tactile fields, a novel 3D representation that maps spatial locations to the expected tactile response upon contact.<n>Our model predicts these neural tactile fields from a single monocular RGB image -- the first method to do so.<n>When integrated with off-the-shelf path planners, neural tactile fields enable robots to generate paths that avoid high-resistance objects.
• Score: 14.002981599280787
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Robots operating in the real world must plan through environments that deform, yield, and reconfigure under contact, requiring interaction-aware 3D representations that extend beyond static geometric occupancy. To address this, we introduce neural tactile fields, a novel 3D representation that maps spatial locations to the expected tactile response upon contact. Our model predicts these neural tactile fields from a single monocular RGB image -- the first method to do so. When integrated with off-the-shelf path planners, neural tactile fields enable robots to generate paths that avoid high-resistance objects while deliberately routing through low-resistance regions (e.g. foliage), rather than treating all occupied space as equally impassable. Empirically, our learning framework improves volumetric 3D reconstruction by $85.8\%$ and surface reconstruction by $26.7\%$ compared to state-of-the-art monocular 3D reconstruction methods (LRM and Direct3D).

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