5 citations · 9 across the 6 of their papers we have counts for
4 papers · 1 filter
eFlesh: Highly customizable Magnetic Touch Sensing using Cut-Cell Microstructures
Venkatesh Pattabiraman, Zizhou Huang, Daniele Panozzo +3
If human experience is any guide, operating effectively in unstructured environments -- like homes and offices -- requires robots to sense the forces during physical interaction. Y…
Feel the Force: Contact-Driven Learning from Humans
Ademi Adeniji, Zhuoran Chen, Vincent Liu +5
Controlling fine-grained forces during manipulation remains a core challenge in robotics. While robot policies learned from robot-collected data or simulation show promise, they st…
Learning Precise, Contact-Rich Manipulation through Uncalibrated Tactile Skins
Venkatesh Pattabiraman, Yifeng Cao, Siddhant Haldar +2
While visuomotor policy learning has advanced robotic manipulation, precisely executing contact-rich tasks remains challenging due to the limitations of vision in reasoning about p…
AnySkin: Plug-and-play Skin Sensing for Robotic Touch
Raunaq Bhirangi, Venkatesh Pattabiraman, Enes Erciyes +3
While tactile sensing is widely accepted as an important and useful sensing modality, its use pales in comparison to other sensory modalities like vision and proprioception. AnySki…