mlsanityData to 7 Oct 2026

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

arXiv 2210.15658 ↗First posted 27 Oct 2022cs.RO cs.LGcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 20 of its 59 references that are in the map. First posted on arXiv 27 Oct 2022.

Builds on

20 of 59 references.

References · 20

  1. 2017Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrationscited by 685
  2. 2018Learning Dexterous In-Hand Manipulationcited by 643
  3. 2020Transporter Networks: Rearranging the Visual World for Robotic Manipulationcited by 342
  4. 2016Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collectioncited by 312
  5. 2015Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hourscited by 208
  6. 2019Deep Dynamics Models for Learning Dexterous Manipulationcited by 200
  7. 2020DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulationcited by 164
  8. 2021A System for General In-Hand Object Re-Orientationcited by 155
  9. 2022DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Realitycited by 136
  10. 2018Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Costcited by 79
  11. 2019ROBEL: Robotics Benchmarks for Learning with Low-Cost Robotscited by 70
  12. 2018GelSlim: A High-Resolution, Compact, Robust, and Calibrated Tactile-sensing Fingercited by 50
8 more
  1. 2021ReSkin: versatile, replaceable, lasting tactile skinscited by 33
  2. 2016Learning Dexterous Manipulation Policies from Experience and Imitationcited by 32
  3. 2020TriFinger: An Open-Source Robot for Learning Dexteritycited by 31
  4. 2019Quantile QT-Opt for Risk-Aware Vision-Based Robotic Graspingcited by 27
  5. 2022Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learningcited by 22
  6. 2020Swoosh! Rattle! Thump! -- Actions that Soundcited by 15
  7. 2013A Compliant, Underactuated Hand for Robust Manipulationcited by 8
  8. 2022Multi-Fingered In-Hand Manipulation with Various Object Properties Using Graph Convolutional Networks and Distributed Tactile Sensorscited by 5

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Citing papers per year: 2024: 3; 2025: 4.

7 papers.