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All the Feels: A Dexterous Hand with Large-Area Tactile Sensing

Raunaq Mahesh Bhirangi, Abigail DeFranco, Jacob Adkins, Carmel Majidi, Abhinav Gupta, Tess Hellebrekers, Vikash Kumar

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Abstract

High cost and lack of reliability have precluded the widespread adoption of dexterous hands in robotics. Furthermore, the lack of a viable tactile sensor capable of sensing over the entire area of the hand impedes the rich, low- level feedback that would improve the learning of dexterous manipulation skills. This paper introduces an inexpensive, modular, and robust platform - the D’Manus - aimed at resolving these challenges while satisfying the large-scale data collection demands of deep robot learning paradigms. Studies on human manipulation point to the criticality of low-level tactile feedback in performing everyday dexterous tasks. The D’Manus comes with ReSkin sensing on the entire surface of the palm as well as the fingertips. We also demonstrate the generalizability of tactile models trained with the fully integrated system in a tactile-aware task - bin-picking and sorting. Code, documentation, design files, detailed assembly instructions, trained models, task videos, and all supplemen- tary materials required to recreate the setup can be found on https://sites.google.com/view/dmanus

Index terms

Grippers and Other End-Effectors Force and Tactile Sensing Soft Sensors and Actuators