# DTact: A Vision-Based Tactile Sensor that Measures High-Resolution 3D Geometry Directly from Darkness

arXiv: https://arxiv.org/abs/2209.13916 · HTML: https://mlsanity.com/paper/2209.13916/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Sep 2022.

## Built on by (most cited first, 9 of 9)

- [Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI](https://mlsanity.com/paper/2407.06886/) (2024)
- [Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation](https://mlsanity.com/paper/2503.02881/) (2025)
- [General In-Hand Object Rotation with Vision and Touch](https://mlsanity.com/paper/2309.09979/) (2023)
- [AcTExplore: Active Tactile Exploration of Unknown Objects](https://mlsanity.com/paper/2310.08745/) (2023)
- [LeTac-MPC: Learning Model Predictive Control for Tactile-reactive Grasping](https://mlsanity.com/paper/2403.04934/) (2024)
- [NLiPsCalib: An Efficient Calibration Framework for High-Fidelity 3D Reconstruction of Curved Visuotactile Sensors](https://mlsanity.com/paper/2603.09319/) (2026)
- [Seeing Touch from Motion: A Unified Modality-Aware Visuo-Tactile Policy with Tactile Motion Correlation](https://mlsanity.com/paper/2606.29941/) (2026)
- [Towards Design and Development of an ArUco Markers-Based Quantitative Surface Tactile Sensor](https://mlsanity.com/paper/2310.08398/) (2023)
- [Robot Learning with Visual Predicted Force](https://mlsanity.com/paper/2610.04741/) (2026)

## 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.