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Metasurface-enhanced light detection and ranging technology

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 robot...

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Autores principales: Juliano Martins, Renato, Marinov, Emil, Youssef, M. Aziz Ben, Kyrou, Christina, Joubert, Mathilde, Colmagro, Constance, Gâté, Valentin, Turbil, Colette, Coulon, Pierre-Marie, Turover, Daniel, Khadir, Samira, Giudici, Massimo, Klitis, Charalambos, Sorel, Marc, Genevet, Patrice
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523074/
https://www.ncbi.nlm.nih.gov/pubmed/36175421
http://dx.doi.org/10.1038/s41467-022-33450-2
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author Juliano Martins, Renato
Marinov, Emil
Youssef, M. Aziz Ben
Kyrou, Christina
Joubert, Mathilde
Colmagro, Constance
Gâté, Valentin
Turbil, Colette
Coulon, Pierre-Marie
Turover, Daniel
Khadir, Samira
Giudici, Massimo
Klitis, Charalambos
Sorel, Marc
Genevet, Patrice
author_facet Juliano Martins, Renato
Marinov, Emil
Youssef, M. Aziz Ben
Kyrou, Christina
Joubert, Mathilde
Colmagro, Constance
Gâté, Valentin
Turbil, Colette
Coulon, Pierre-Marie
Turover, Daniel
Khadir, Samira
Giudici, Massimo
Klitis, Charalambos
Sorel, Marc
Genevet, Patrice
author_sort Juliano Martins, Renato
collection PubMed
description 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.
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spelling pubmed-95230742022-10-01 Metasurface-enhanced light detection and ranging technology Juliano Martins, Renato Marinov, Emil Youssef, M. Aziz Ben Kyrou, Christina Joubert, Mathilde Colmagro, Constance Gâté, Valentin Turbil, Colette Coulon, Pierre-Marie Turover, Daniel Khadir, Samira Giudici, Massimo Klitis, Charalambos Sorel, Marc Genevet, Patrice Nat Commun Article 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. Nature Publishing Group UK 2022-09-29 /pmc/articles/PMC9523074/ /pubmed/36175421 http://dx.doi.org/10.1038/s41467-022-33450-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Juliano Martins, Renato
Marinov, Emil
Youssef, M. Aziz Ben
Kyrou, Christina
Joubert, Mathilde
Colmagro, Constance
Gâté, Valentin
Turbil, Colette
Coulon, Pierre-Marie
Turover, Daniel
Khadir, Samira
Giudici, Massimo
Klitis, Charalambos
Sorel, Marc
Genevet, Patrice
Metasurface-enhanced light detection and ranging technology
title Metasurface-enhanced light detection and ranging technology
title_full Metasurface-enhanced light detection and ranging technology
title_fullStr Metasurface-enhanced light detection and ranging technology
title_full_unstemmed Metasurface-enhanced light detection and ranging technology
title_short Metasurface-enhanced light detection and ranging technology
title_sort metasurface-enhanced light detection and ranging technology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523074/
https://www.ncbi.nlm.nih.gov/pubmed/36175421
http://dx.doi.org/10.1038/s41467-022-33450-2
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