Research

DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation

June 1, 2020

Abstract

Despite decades of research, general purpose inhand manipulation remains one of the unsolved challenges of robotics. One of the contributing factors that limit current robotic manipulation systems is the difficulty of precisely sensing contact forces – sensing and reasoning about contact forces are crucial to accurately control interactions with the environment. As a step towards enabling better robotic manipulation, we introduce DIGIT, an inexpensive, compact, and high-resolution tactile sensor geared towards in-hand manipulation. DIGIT improves upon past vision-based tactile sensors by miniaturizing the form factor to be mountable on multi-fingered hands, and by providing several design improvements that result in an easier, more repeatable manufacturing process, and enhanced reliability. We demonstrate the capabilities of the DIGIT sensor by training deep neural network model-based controllers to manipulate glass marbles in-hand with a multi-finger robotic hand. To provide the robotic community access to reliable and low-cost tactile sensors, we open-source the DIGIT design at www.digit.ml.

Download the Paper

AUTHORS

Written by

Mike Lambeta

Po-Wei Chou

Stephen Tian

Brian Yang

Benjamin Maloon

Victoria Rose Most

Dave Stroud

Raymond Santos

Ahmad Byagowi

Gregg Kammerer

Dinesh Jayaraman

Roberto Calandra

Publisher

IEEE Robotics and Automation Letters (RA-L)

Related Publications

February 27, 2026

Human & Machine Intelligence

Unified Vision–Language Modeling via Concept Space Alignment

Yifu Qiu, Paul-Ambroise Duquenne, Holger Schwenk

February 27, 2026

February 26, 2026

Conversational AI

Learning Personalized Agents from Human Feedback

Kaiqu Liang, Julia Kruk, Shengyi Qian, Xianjun Yang, Shengjie Bi, Shaoliang Nie, Michael Zhang, Lijuan Liu, Jaime Fernández Fisac, Shuyan Zhou, Saghar Hosseini

February 26, 2026

February 11, 2026

Computer Vision

UniT: Unified Multimodal Chain-of-Thought Test-time Scaling

Leon Liangyu Chen, Haoyu Ma, Zhipeng Fan, Ziqi Huang, Animesh Sinha, Xiaoliang Dai, Jialiang Wang, Zecheng He, Jianwei Yang, Chunyuan Li, Junzhe Sun, Chu Wang, Serena Yeung-Levy, Felix Juefei-Xu

February 11, 2026

December 18, 2025

Computer Vision

Pixel Seal: Adversarial-only training for invisible image and video watermarking

Tomáš Souček, Pierre Fernandez, Hady Elsahar, Sylvestre Rebuffi, Valeriu Lacatusu, Tuan Tran, Tom Sander, Alexandre Mourachko

December 18, 2025

October 31, 2019

NLP

Facebook AI's WAT19 Myanmar-English Translation Task Submission

Peng-Jen Chen, Jiajun Shen, Matt Le, Vishrav Chaudhary, Ahmed El-Kishky, Guillaume Wenzek, Myle Ott, Marc’Aurelio Ranzato

October 31, 2019

October 27, 2019

Order-Aware Generative Modeling Using the 3D-Craft Dataset | Facebook AI Research

Zhuoyuan Chen, Demi Guo, Tong Xiao, Saining Xie, Xinlei Chen, Haonan Yu, Jonathan Gray, Kavya Srinet, Haoqi Fan, Jerry Ma, Charles R. Qi, Shubham Tulsiani, Arthur Szlam, Larry Zitnick

October 27, 2019

April 25, 2020

Energy-Based Models for Atomic-Resolution Protein Conformations | Facebook AI Research

Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives

April 25, 2020

June 11, 2019

Computer Vision

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero | Facebook AI Research

Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, Larry Zitnick

June 11, 2019

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.