mlsanityData to 14 Oct 2026

SoTa: Soft Tactile Skins for Dexterous Manipulation

arXiv 2610.02338 ↗First posted 1 Oct 2026cs.RO cs.LGcited by 0

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Abstract (arXiv)

A growing body of work suggests that tactile sensing gives robot policies contact information that complements vision in dexterous manipulation. However, visuo-tactile robot data remains scarce: dexterous demonstrations require teleoperating robots, which limits dataset scale. Human demonstrations are far cheaper to collect and offer a path to scale this data, but only if human and robot hands carry tactile sensors with corresponding signals. This requires sensors that conform to different hand geometries, cover the full hand, and share a common layout across embodiments. We present SoTa, a low-cost capacitive tactile skin that provides full-hand coverage on humans and robots while preserving a shared layout of 202 taxels across corresponding finger and palm regions. Our multilayer design with fabric electrodes enables in-house fabrication of thin, soft skins with customizable geometry for under 10 in materials per skin. The sensor retains over 97% of its initial response span after 10,000 loading-unloading cycles with traces retaining continuity through 1,280 tight-fist folding cycles. The shared taxel layout supports human-robot co-training with a common tactile encoder and no learned cross-sensor mapping. Across three contact-rich manipulation tasks, tactile observations improve in-distribution success over vision-only policies. With a fixed robot demonstration budget, adding human demonstrations more than doubles mean success across eight evaluation conditions, from 22.8% to 45.9%, improving success in all five out-of-distribution conditions. We plan to open-source the resources needed to fabricate and operate these skins.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 41 of its 46 references that are in the map. First posted on arXiv 1 Oct 2026.

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41 of 46 references.

References · 41

  1. 2024π0: A Vision-Language-Action Flow Model for General Robot Controlcited by 2,407
  2. 2025π0.5: a Vision-Language-Action Model with Open-World Generalizationcited by 1,761
  3. 2023Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardwarecited by 1,568
  4. 2024DROID: A Large-Scale In-The-Wild Robot Manipulation Datasetcited by 852
  5. 2023BridgeData V2: A Dataset for Robot Learning at Scalecited by 657
  6. 2024Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperationcited by 391
  7. 2023Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulationcited by 364
  8. 2024EgoMimic: Scaling Imitation Learning via Egocentric Videocited by 175
  9. 2023AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation Systemcited by 152
  10. 2019DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm Systemcited by 114
  11. 2023General In-Hand Object Rotation with Vision and Touchcited by 99
  12. 2025ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulationcited by 91
29 more
  1. 2025Humanoid Policy ~ Human Policycited by 78
  2. 2024Learning Visuotactile Skills with Two Multifingered Handscited by 76
  3. 20243D-ViTac: Learning Fine-Grained Manipulation with Visuo-Tactile Sensingcited by 72
  4. 2025DexUMI: Using Human Hand as the Universal Manipulation Interface for Dexterous Manipulationcited by 66
  5. 2023Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensingcited by 56
  6. 2025Masquerade: Learning from In-the-wild Human Videos using Data-Editingcited by 43
  7. 2025Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Groundingcited by 42
  8. 2025Emergence of Human to Robot Transfer in Vision-Language-Action Modelscited by 42
  9. 2021ReSkin: versatile, replaceable, lasting tactile skinscited by 35
  10. 2023MimicTouch: Leveraging Multi-modal Human Tactile Demonstrations for Contact-rich Manipulationcited by 34
  11. 2025TA-VLA: Elucidating the Design Space of Torque-aware Vision-Language-Action Modelscited by 32
  12. 2023The Power of the Senses: Generalizable Manipulation from Vision and Touch through Masked Multimodal Learningcited by 26
  13. 2024Bimanual Dexterity for Complex Taskscited by 25
  14. 2025DexForce: Extracting Force-informed Actions from Kinesthetic Demonstrations for Dexterous Manipulationcited by 24
  15. 2024AnySkin: Plug-and-play Skin Sensing for Robotic Touchcited by 23
  16. 2026EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Datacited by 20
  17. 2025DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulationcited by 19
  18. 2025OPENTOUCH: Bringing Full-Hand Touch to Real-World Interactioncited by 15
  19. 2026FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors for Contact-Rich Manipulationcited by 13
  20. 2024Learning Precise, Contact-Rich Manipulation through Uncalibrated Tactile Skinscited by 12
  21. 2025OSMO: Open-Source Tactile Glove for Human-to-Robot Skill Transfercited by 10
  22. 2022All the Feels: A dexterous hand with large-area tactile sensingcited by 8
  23. 2025Feel the Force: Contact-Driven Learning from Humanscited by 8
  24. 2025Fits like a Flex-Glove: Automatic Design of Personalized FPCB-Based Tactile Sensing Glovescited by 6
  25. 2026TactAlign: Human-to-Robot Policy Transfer via Tactile Alignmentcited by 6
  26. 2025Self-supervised perception for tactile skin covered dexterous handscited by 5
  27. 2025UniTacHand: Unified Spatio-Tactile Representation for Human to Robotic Hand Skill Transfercited by 5
  28. 2025DexSkin: High-Coverage Conformable Robotic Skin for Learning Contact-Rich Manipulationcited by 4
  29. 2026Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Themcited by 2

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