SoTa: Soft Tactile Skins for Dexterous Manipulation
cs.RO, cs.LG
Submitted: 2026-10-01
Updated: 2026-10-01
Comments: The first three authors contributed equally. Project website: https://sota-skin.github.io
Project page: https://sota-skin.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation
- Learning Precise, Contact-Rich Manipulation through Uncalibrated Tactile Skins
- ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulation
- Feel the Force: Contact-Driven Learning from Humans
- ReSkin: versatile, replaceable, lasting tactile skins
- Self-supervised perception for tactile skin covered dexterous hands
- MimicTouch: Leveraging Multi-modal Human Tactile Demonstrations for Contact-rich Manipulation
- DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation
- OSMO: Open-Source Tactile Glove for Human-to-Robot Skill Transfer
- OPENTOUCH: Bringing Full-Hand Touch to Real-World Interaction
- UniTacHand: Unified Spatio-Tactile Representation for Human to Robotic Hand Skill Transfer
- TactAlign: Human-to-Robot Policy Transfer via Tactile Alignment
- Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Them
- FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors for Contact-Rich Manipulation
- Emergence of Human to Robot Transfer in Vision-Language-Action Models
- Humanoid Policy ~ Human Policy
- Masquerade: Learning from In-the-wild Human Videos using Data-Editing
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