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All the Feels: A dexterous hand with large-area tactile sensing

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arxiv 2210.15658 v3 pith:VKOH4YXF submitted 2022-10-27 cs.RO cs.LG

classification cs.ROcs.LG
keywords dexteroustactiledmanussensingentirefeedbackhandlack
verification ladder T0 review T1 audit T2 compute T3 formal
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High cost and lack of reliability has 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 learning of dexterous manipulation skills. This paper introduces an inexpensive, modular, robust, and scalable platform -- the DManus -- aimed at resolving these challenges while satisfying the large-scale data collection capabilities demanded by deep robot learning paradigms. Studies on human manipulation point to the criticality of low-level tactile feedback in performing everyday dexterous tasks. The DManus comes with ReSkin sensing on the entire surface of the palm as well as the fingertips. We demonstrate effectiveness of 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 supplementary materials required to recreate the setup can be found on https://sites.google.com/view/roboticsbenchmarks/platforms/dmanus.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Handroid: Bridging Dexterous Hand and Humanoid

    cs.RO 2026-07 conditional novelty 7.0 of 10

    A single 27-DoF body doubles as an anthropomorphic dexterous hand and a 0.33 m desktop humanoid, with a unified control stack for manipulation, locomotion, and embodiment switching.

  2. CRAFT: A Tendon-Driven Hand with Hybrid Hard-Soft Compliance

    cs.RO 2026-03 conditional novelty 5.0 of 10

    Hybrid hard-soft tendon hand with rolling joints improves strength and fragile teleop over a rigid baseline, covers 33/33 Feix grasps, and costs under $600 open-source.

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