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Multi-modal deformation and temperature sensing for context-sensitive machines

Engineering and Technology

Multi-modal deformation and temperature sensing for context-sensitive machines

R. Baines, F. Zuliani, et al.

Explore the groundbreaking ChromoSense technology, capable of decoding complex stimuli like bending and temperature changes through a unique light-based sensing method. This innovative approach enhances the understanding of human-robot interactions and pushes the boundaries of machine proprioception. Research conducted by Robert Baines, Fabio Zuliani, Neil Chennoufi, Sagar Joshi, Rebecca Kramer-Bottiglio, and Jamie Paik.

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Playback language: English
Abstract
This paper introduces ChromoSense, a novel sensing technology capable of decoding omnidirectional bending, compression, stretch, binary temperature changes, and combinations thereof. It leverages the chromaticity and intensity of light traveling through a patterned elastomer doped with functional dyes, offering a one-to-one mapping between stimuli and sensor output. The sensor's high information density allows for deciphering complex human-robot and robot-environmental interactions, moving towards biologically inspired proprioception in machines.
Publisher
Nature Communications
Published On
Nov 18, 2023
Authors
Robert Baines, Fabio Zuliani, Neil Chennoufi, Sagar Joshi, Rebecca Kramer-Bottiglio, Jamie Paik
Tags
ChromoSense
sensing technology
omnidirectional bending
human-robot interactions
proprioception
functional dyes
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