most citedDexterity from Touch: Self-Supervised Pre-Training of Tactile Representations with Robotic Play

8 citations · 8 across the 3 of their papers we have counts for

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cs.RO2023

See to Touch: Learning Tactile Dexterity through Visual Incentives

Irmak Guzey, Yinlong Dai, Ben Evans +2

Equipping multi-fingered robots with tactile sensing is crucial for achieving the precise, contact-rich, and dexterous manipulation that humans excel at. However, relying solely on…

cs.RO2023★ 8 cited

Dexterity from Touch: Self-Supervised Pre-Training of Tactile Representations with Robotic Play

Irmak Guzey, Ben Evans, Soumith Chintala +1

Teaching dexterity to multi-fingered robots has been a longstanding challenge in robotics. Most prominent work in this area focuses on learning controllers or policies that either…