# OmniTact: A Multi-Directional High Resolution Touch Sensor

arXiv: https://arxiv.org/abs/2003.06965 · HTML: https://mlsanity.com/paper/2003.06965/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Mar 2020.

## Built on by (most cited first, 28 of 28)

- [Rotating without Seeing: Towards In-hand Dexterity through Touch](https://mlsanity.com/paper/2303.10880/) (2023)
- [ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfer](https://mlsanity.com/paper/2204.02389/) (2022)
- [3D-ViTac: Learning Fine-Grained Manipulation with Visuo-Tactile Sensing](https://mlsanity.com/paper/2410.24091/) (2024)
- [ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations](https://mlsanity.com/paper/2109.07991/) (2021)
- [GelSight Wedge: Measuring High-Resolution 3D Contact Geometry with a Compact Robot Finger](https://mlsanity.com/paper/2106.08851/) (2021)
- [Neural feels with neural fields: Visuo-tactile perception for in-hand manipulation](https://mlsanity.com/paper/2312.13469/) (2023)
- [AnySkin: Plug-and-play Skin Sensing for Robotic Touch](https://mlsanity.com/paper/2409.08276/) (2024)
- [Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image Translation](https://mlsanity.com/paper/2106.08796/) (2021)
- [Learning to Read Braille: Bridging the Tactile Reality Gap with Diffusion Models](https://mlsanity.com/paper/2304.01182/) (2023)
- [DenseTact: Optical Tactile Sensor for Dense Shape Reconstruction](https://mlsanity.com/paper/2201.01367/) (2022)
- [TANDEM: Learning Joint Exploration and Decision Making with Tactile Sensors](https://mlsanity.com/paper/2203.00798/) (2022)
- [DexTouch: Learning to Seek and Manipulate Objects with Tactile Dexterity](https://mlsanity.com/paper/2401.12496/) (2024)
- [GelSight Svelte: A Human Finger-shaped Single-camera Tactile Robot Finger with Large Sensing Coverage and Proprioceptive Sensing](https://mlsanity.com/paper/2309.10885/) (2023)
- [Sim2Real Manipulation on Unknown Objects with Tactile-based Reinforcement Learning](https://mlsanity.com/paper/2403.12170/) (2024)
- [A soft thumb-sized vision-based sensor with accurate all-round force perception](https://mlsanity.com/paper/2111.05934/) (2021)
- [Multimodal and Force-Matched Imitation Learning with a See-Through Visuotactile Sensor](https://mlsanity.com/paper/2311.01248/) (2023)
- [FlexiTac: A Low-Cost, Open-Source, Scalable Tactile Sensing Solution for Robotic Systems](https://mlsanity.com/paper/2604.28156/) (2026)
- [Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing](https://mlsanity.com/paper/2210.04026/) (2022)
- [Learning Intuitive Physics with Multimodal Generative Models](https://mlsanity.com/paper/2101.04454/) (2021)
- [PyTouch: A Machine Learning Library for Touch Processing](https://mlsanity.com/paper/2105.12791/) (2021)
- [Learning to Synthesize Volumetric Meshes from Vision-based Tactile Imprints](https://mlsanity.com/paper/2203.15155/) (2022)
- [GelFlow: Self-supervised Learning of Optical Flow for Vision-Based Tactile Sensor Displacement Measurement](https://mlsanity.com/paper/2309.06735/) (2023)
- [Optimizing BioTac Simulation for Realistic Tactile Perception](https://mlsanity.com/paper/2404.10425/) (2024)
- [NLiPsCalib: An Efficient Calibration Framework for High-Fidelity 3D Reconstruction of Curved Visuotactile Sensors](https://mlsanity.com/paper/2603.09319/) (2026)
- [Tactile-based Multimodal Fusion in Embodied Intelligence: A Survey of Vision, Language, and Contact-Driven Paradigms](https://mlsanity.com/paper/2605.17336/) (2026)
- [RETRO: REthinking Tactile Representation Learning with Material PriOrs](https://mlsanity.com/paper/2505.14319/) (2025)
- [Towards Design and Development of an ArUco Markers-Based Quantitative Surface Tactile Sensor](https://mlsanity.com/paper/2310.08398/) (2023)
- [In-Vivo Skin 3-D Surface Reconstruction and Wrinkle Depth Estimation using Handheld High Resolution Tactile Sensing](https://mlsanity.com/paper/2509.11385/) (2025)

## Abstract (arXiv)

Incorporating touch as a sensing modality for robots can enable finer and more robust manipulation skills. Existing tactile sensors are either flat, have small sensitive fields or only provide low-resolution signals. In this paper, we introduce OmniTact, a multi-directional high-resolution tactile sensor. OmniTact is designed to be used as a fingertip for robotic manipulation with robotic hands, and uses multiple micro-cameras to detect multi-directional deformations of a gel-based skin. This provides a rich signal from which a variety of different contact state variables can be inferred using modern image processing and computer vision methods. We evaluate the capabilities of OmniTact on a challenging robotic control task that requires inserting an electrical connector into an outlet, as well as a state estimation problem that is representative of those typically encountered in dexterous robotic manipulation, where the goal is to infer the angle of contact of a curved finger pressing against an object. Both tasks are performed using only touch sensing and deep convolutional neural networks to process images from the sensor's cameras. We compare with a state-of-the-art tactile sensor that is only sensitive on one side, as well as a state-of-the-art multi-directional tactile sensor, and find that OmniTact's combination of high-resolution and multi-directional sensing is crucial for reliably inserting the electrical connector and allows for higher accuracy in the state estimation task. Videos and supplementary material can be found at https://sites.google.com/berkeley.edu/omnitact