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Metasurface-enhanced light detection and ranging technology
by
Giudici, Massimo
, Joubert, Mathilde
, Gâté, Valentin
, Juliano Martins, Renato
, Klitis, Charalambos
, Turbil, Colette
, Khadir, Samira
, Colmagro, Constance
, Youssef, M. Aziz Ben
, Coulon, Pierre-Marie
, Turover, Daniel
, Kyrou, Christina
, Genevet, Patrice
, Marinov, Emil
, Sorel, Marc
in
639/624/1107/510
/ 639/624/399/1015
/ 639/925/930/2735
/ Algorithms
/ Computer Science
/ Computer vision
/ Computer Vision and Pattern Recognition
/ Decision making
/ Deflectors
/ Eye
/ Field of view
/ Fovea
/ Humanities and Social Sciences
/ Imaging
/ Lidar
/ Machine learning
/ Machine vision
/ Metasurfaces
/ Mimicry
/ multidisciplinary
/ Optical components
/ Optimization
/ Retina
/ Robotics
/ Science
/ Science (multidisciplinary)
2022
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Metasurface-enhanced light detection and ranging technology
by
Giudici, Massimo
, Joubert, Mathilde
, Gâté, Valentin
, Juliano Martins, Renato
, Klitis, Charalambos
, Turbil, Colette
, Khadir, Samira
, Colmagro, Constance
, Youssef, M. Aziz Ben
, Coulon, Pierre-Marie
, Turover, Daniel
, Kyrou, Christina
, Genevet, Patrice
, Marinov, Emil
, Sorel, Marc
in
639/624/1107/510
/ 639/624/399/1015
/ 639/925/930/2735
/ Algorithms
/ Computer Science
/ Computer vision
/ Computer Vision and Pattern Recognition
/ Decision making
/ Deflectors
/ Eye
/ Field of view
/ Fovea
/ Humanities and Social Sciences
/ Imaging
/ Lidar
/ Machine learning
/ Machine vision
/ Metasurfaces
/ Mimicry
/ multidisciplinary
/ Optical components
/ Optimization
/ Retina
/ Robotics
/ Science
/ Science (multidisciplinary)
2022
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Metasurface-enhanced light detection and ranging technology
by
Giudici, Massimo
, Joubert, Mathilde
, Gâté, Valentin
, Juliano Martins, Renato
, Klitis, Charalambos
, Turbil, Colette
, Khadir, Samira
, Colmagro, Constance
, Youssef, M. Aziz Ben
, Coulon, Pierre-Marie
, Turover, Daniel
, Kyrou, Christina
, Genevet, Patrice
, Marinov, Emil
, Sorel, Marc
in
639/624/1107/510
/ 639/624/399/1015
/ 639/925/930/2735
/ Algorithms
/ Computer Science
/ Computer vision
/ Computer Vision and Pattern Recognition
/ Decision making
/ Deflectors
/ Eye
/ Field of view
/ Fovea
/ Humanities and Social Sciences
/ Imaging
/ Lidar
/ Machine learning
/ Machine vision
/ Metasurfaces
/ Mimicry
/ multidisciplinary
/ Optical components
/ Optimization
/ Retina
/ Robotics
/ Science
/ Science (multidisciplinary)
2022
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Metasurface-enhanced light detection and ranging technology
Journal Article
Metasurface-enhanced light detection and ranging technology
2022
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Overview
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.
Mimicking human vision with metasurfaces, the authors propose a new paradigm for high field of view and ultrafast LiDAR, achieving performances also relevant for the next generation of imaging system for ADAS and robotic systems.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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