Metasurface-enhanced light detection and ranging technology

Juliano Martins, R. et al. (2022) Metasurface-enhanced light detection and ranging technology. Nature Communications, 13, 5724. (doi: 10.1038/s41467-022-33450-2) (PMID:36175421) (PMCID:PMC9523074)

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Deploying advanced imaging solutions to robotic and autonomous systems by mimicking human vision requires simultaneous acquisition of multiple fields of views, named the peripheral and fovea regions. Among 3D computer vision techniques, LiDAR is currently considered at the industrial level for robotic vision. Notwithstanding the efforts on LiDAR integration and optimization, commercially available devices have slow frame rate and low resolution, notably limited by the performance of mechanical or solid-state deflection systems. Metasurfaces are versatile optical components that can distribute the optical power in desired regions of space. Here, we report on an advanced LiDAR technology that leverages from ultrafast low FoV deflectors cascaded with large area metasurfaces to achieve large FoV (150°) and high framerate (kHz) which can provide simultaneous peripheral and central imaging zones. The use of our disruptive LiDAR technology with advanced learning algorithms offers perspectives to improve perception and decision-making process of ADAS and robotic systems.

Item Type:Articles
Additional Information:This work was financially supported by the European Research Council proof of concept (ERC POC) under the European Union’s Horizon 2020 research and innovation program (Project i-LiDAR, grant number 874986), the CNRS prématuration, and the UCA Innovation Program (2020 startup deepTech) and the French defense procurement agency under the ANR ASTRID Maturation program, grant agreement number ANR-18-ASMA-0006. CK and MS acknowledge inputs of the technical staff at the James Watt Nanofabrication Centre at Glasgow University. C. Kyrou has been supported with a postdoctoral fellowship grant by the Bodossaki Foundation (Athens, Greece).
Glasgow Author(s) Enlighten ID:Klitis, Dr Charalambos and Sorel, Professor Marc
Authors: Juliano Martins, R., Marinov, E., Youssef, M. A. B., Kyrou, C., Joubert, M., Colmagro, C., Gâté, V., Turbil, C., Coulon, P.-M., Turover, D., Khadir, S., Giudici, M., Klitis, C., Sorel, M., and Genevet, P.
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
Journal Name:Nature Communications
Publisher:Nature Publishing Group UK
ISSN (Online):2041-1723
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Nature Communications 13(1):5724
Publisher Policy:Reproduced under a Creative Commons License

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