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20242026
most citedInvariant neuromorphic representations of tactile stimuli improve robustness of a real-time texture classification system

5 citations · 8 across the 4 of their papers we have counts for

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cs.RO2026

OpenTac: An Open Ecosystem for Customizable, Scalable, and Transferable 3D Tactile Sensing

Ariel Slepyan, Geeta Chandra Raju Bethala, Jiafeng Gu +12

We present OpenTac, a novel sensor and a full-stack ecosystem for tactile skins that are highly customizable, scalable, and readily deployed in downstream robot control and learnin…

cs.RO2025

Single-Pixel Tactile Skin via Compressive Sampling

Ariel Slepyan, Laura Xing, Rudy Zhang +1

Development of large-area, high-speed electronic skins is a grand challenge for robotics, prosthetics, and human-machine interfaces, but is fundamentally limited by wiring complexi…

cs.RO2024

At First Contact: Stiffness Estimation Using Vibrational Information for Prosthetic Grasp Modulation

Anway S. Pimpalkar, Ariel Slepyan, Nitish V. Thakor

Stiffness estimation is crucial for delicate object manipulation in robotic and prosthetic hands but remains challenging due to dependence on force and displacement measurement and…

cs.RO2024★ 5 cited

Invariant neuromorphic representations of tactile stimuli improve robustness of a real-time texture classification system

Mark M. Iskarous, Zan Chaudhry, Fangjie Li +7

Humans have an exquisite sense of touch which robotic and prosthetic systems aim to recreate. We developed algorithms to create neuron-like (neuromorphic) spiking representations o…

cs.RO2024

Adaptive Compressive Tactile Subsampling: Enabling High Spatiotemporal Resolution in Scalable Robotic Skin

Ariel Slepyan, Dian Li, Hongjun Cai +5

Robots require full-body, high-resolution tactile sensing to operate safely in unstructured environments, enabling reflexive responses and closed-loop control. However, the pixel c…