DTact: A Vision-Based Tactile Sensor that Measures High-Resolution 3D Geometry Directly from Darkness
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Abstract (arXiv)
Vision-based tactile sensors that can measure 3D geometry of the contacting objects are crucial for robots to perform dexterous manipulation tasks. However, the existing sensors are usually complicated to fabricate and delicate to extend. In this work, we novelly take advantage of the reflection property of semitransparent elastomer to design a robust, low-cost, and easy-to-fabricate tactile sensor named DTact. DTact measures high-resolution 3D geometry accurately from the darkness shown in the captured tactile images with only a single image for calibration. In contrast to previous sensors, DTact is robust under various illumination conditions. Then, we build prototypes of DTact that have non-planar contact surfaces with minimal extra efforts and costs. Finally, we perform two intelligent robotic tasks including pose estimation and object recognition using DTact, in which DTact shows large potential in applications.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Sep 2022.
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Citing papers per year: 2023: 3; 2024: 2; 2025: 1; 2026: 3.
9 papers.
- 2024Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AIcited by 179
- 2025Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulationcited by 108
- 2023General In-Hand Object Rotation with Vision and Touchcited by 99
- 2023AcTExplore: Active Tactile Exploration of Unknown Objectscited by 12
- 2024LeTac-MPC: Learning Model Predictive Control for Tactile-reactive Graspingcited by 4
- 2026NLiPsCalib: An Efficient Calibration Framework for High-Fidelity 3D Reconstruction of Curved Visuotactile Sensorscited by 2
- 2026Seeing Touch from Motion: A Unified Modality-Aware Visuo-Tactile Policy with Tactile Motion Correlationcited by 2
- 2023Towards Design and Development of an ArUco Markers-Based Quantitative Surface Tactile Sensorcited by 0
- 2026Robot Learning with Visual Predicted Forcecited by 0
- 2026Robot Learning with Visual Predicted Force3 Oct 2026
- 2026Seeing Touch from Motion: A Unified Modality-Aware Visuo-Tactile Policy with Tactile Motion Correlation29 Jun 2026
- 2026NLiPsCalib: An Efficient Calibration Framework for High-Fidelity 3D Reconstruction of Curved Visuotactile Sensors10 Mar 2026
- 2025Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation4 Mar 2025
- 2024Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI9 Jul 2024
- 2024LeTac-MPC: Learning Model Predictive Control for Tactile-reactive Grasping7 Mar 2024
- 2023AcTExplore: Active Tactile Exploration of Unknown Objects12 Oct 2023
- 2023Towards Design and Development of an ArUco Markers-Based Quantitative Surface Tactile Sensor12 Oct 2023
- 2023General In-Hand Object Rotation with Vision and Touch18 Sep 2023