3 citations · 3 across the 7 of their papers we have counts for
7 papers
FEEL (Force-Enhanced Egocentric Learning): A Dataset for Physical Action Understanding
Eadom Dessalene, Botao He, Michael Maynord +5
We introduce FEEL (Force-Enhanced Egocentric Learning), the first large-scale dataset pairing force measurements gathered from custom piezoresistive gloves with egocentric video. O…
Monocular Reconstruction of Neural Tactile Fields
Pavan Mantripragada, Siddhanth Deshmukh, Eadom Dessalene +2
Robots operating in the real world must plan through environments that deform, yield, and reconfigure under contact, requiring interaction-aware 3D representations that extend beyo…
EmbodiSwap for Zero-Shot Robot Imitation Learning
Eadom Dessalene, Pavan Mantripragada, Michael Maynord +1
We introduce EmbodiSwap - a method for producing photorealistic synthetic robot overlays over human video. We employ EmbodiSwap for zero-shot imitation learning, bridging the embod…
Extremum Seeking Controlled Wiggling for Tactile Insertion
Levi Burner, Pavan Mantripragada, Gabriele M. Caddeo +3
When humans perform complex insertion tasks such as pushing a cup into a cupboard, routing a cable, or putting a key in a lock, they wiggle the object and adapt the process through…
AcTExplore: Active Tactile Exploration of Unknown Objects
Amir-Hossein Shahidzadeh, Seong Jong Yoo, Pavan Mantripragada +3
Tactile exploration plays a crucial role in understanding object structures for fundamental robotics tasks such as grasping and manipulation. However, efficiently exploring such ob…
GradTac: Spatio-Temporal Gradient Based Tactile Sensing
Kanishka Ganguly, Pavan Mantripragada, Chethan M. Parameshwara +3
Tactile sensing for robotics is achieved through a variety of mechanisms, including magnetic, optical-tactile, and conductive fluid. Currently, the fluid-based sensors have struck…
Grasping in the Dark: Zero-Shot Object Grasping Using Tactile Feedback
Kanishka Ganguly, Behzad Sadrfaridpour, Pavan Mantripragada +3
Grasping and manipulating a wide variety of objects is a fundamental skill that would determine the success and wide spread adaptation of robots in homes. Several end-effector desi…