Digitizing Touch with an Artificial Multimodal Fingertip
Mike Lambeta, Tingfan Wu, Ali Sengul, Victoria Rose Most, Nolan Black,, Kevin Sawyer, Romeo Mercado, Haozhi Qi, Alexander Sohn, Byron Taylor, Norb, Tydingco, Gregg Kammerer, Dave Stroud, Jake Khatha, Kurt Jenkins, Kyle Most,, Neal Stein, Ricardo Chavira, Thomas Craven-Bartle

TL;DR
This paper introduces an advanced artificial fingertip with multimodal sensing, high resolution, and real-time AI processing, enabling superhuman digitization of touch for robotics, VR, prosthetics, and more.
Contribution
The development of a multimodal, high-resolution artificial fingertip with embedded AI for real-time touch perception and reflex-like responses.
Findings
Resolves spatial features as small as 7 micrometers
Senses forces with resolutions of 1.01 mN (normal) and 1.27 mN (shear)
Perceives vibrations up to 10 kHz, heat, and odor
Abstract
Touch is a crucial sensing modality that provides rich information about object properties and interactions with the physical environment. Humans and robots both benefit from using touch to perceive and interact with the surrounding environment (Johansson and Flanagan, 2009; Li et al., 2020; Calandra et al., 2017). However, no existing systems provide rich, multi-modal digital touch-sensing capabilities through a hemispherical compliant embodiment. Here, we describe several conceptual and technological innovations to improve the digitization of touch. These advances are embodied in an artificial finger-shaped sensor with advanced sensing capabilities. Significantly, this fingertip contains high-resolution sensors (~8.3 million taxels) that respond to omnidirectional touch, capture multi-modal signals, and use on-device artificial intelligence to process the data in real time.…
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Taxonomy
TopicsHand Gesture Recognition Systems · Interactive and Immersive Displays · Tactile and Sensory Interactions
