Evidence map›Paper›PMID 36175421›Full record

ArticleNature communications2022

Metasurface-enhanced light detection and ranging technology.

Renato Juliano Martins, Emil Marinov, M Aziz Ben Youssef, Christina Kyrou, Mathilde Joubert, Constance Colmagro, Valentin Gâté, Colette Turbil, Pierre-Marie Coulon, Daniel Turover and 5 more

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

  1. Article
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  7. Review
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  9. Metasurface-based Fourier ptychographic microscopy.Nanophotonics (Berlin, Germany) · 2025
    Article
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  11. Article
  12. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Renato Juliano MartinsUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
Emil MarinovUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
M Aziz Ben YoussefUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
Christina KyrouUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
Mathilde JoubertUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
Constance ColmagroUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
Valentin GâtéNAPA-Technologies, 74160, Archamps, France.
Colette TurbilNAPA-Technologies, 74160, Archamps, France.
Pierre-Marie CoulonUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
Daniel TuroverNAPA-Technologies, 74160, Archamps, France.
Samira KhadirUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France.
Massimo GiudiciUniversité Côte d'Azur, Centre National de La Recherche Scientifique, Institut de Physique de Nice, F-06560, Valbonne, France.
Charalambos KlitisSchool of Engineering, University of Glasgow, Glasgow, G12 8LT, UK.
Marc SorelSchool of Engineering, University of Glasgow, Glasgow, G12 8LT, UK.
Patrice GenevetUniversité Cote d'Azur, CNRS, CRHEA, Rue Bernard Gregory, Sophia Antipolis, 06560, Valbonne, France. Patrice.Genevet@crhea.cnrs.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Optical DevicesTechnologyAlgorithmsFovea CentralisHumansIndustry

Identifiers

PMID36175421
PMCPMC9523074

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.