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Application of a short wave infrared sensor for the perception of mobile robots in harsh weather conditions ; Application d’un capteur infrarouge à ondes courtes pour la perception de robots mobiles dans des conditions météorologiques difficiles

Title: Application of a short wave infrared sensor for the perception of mobile robots in harsh weather conditions ; Application d’un capteur infrarouge à ondes courtes pour la perception de robots mobiles dans des conditions météorologiques difficiles
Authors: Riffard, Alexandre; Labussière, Mathieu; Duthon, Pierre; Aufrère, Romuald
Contributors: Institut Pascal (IP); Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne); Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA); Systèmes de transports intelligents (STI); Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema); This work was supported by the International Research Centre ”Innovative Transport and Production Systems” of the CAP 20-25 I-SITE.; Marc Tommasi; Michaël Perrot; Mikaela Keller; Mohamed Daoudi; Deise Santana Maia
Source: RFIAP2024 - Reconnaissance des Formes, Image, Apprentissage et Perception 2024 ; https://hal.science/hal-04871003 ; RFIAP2024 - Reconnaissance des Formes, Image, Apprentissage et Perception 2024, Jul 2024, Lille, France
Publisher Information: CCSD
Publication Year: 2024
Collection: HAL Clermont Auvergne (Université Blaise Pascal Clermont-Ferrand / Université d'Auvergne)
Subject Terms: SWIR - Short-Wave Infrared; InGaAs; Colloidal quantum dot; Harsh Weather Conditions; [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]; [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]; [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Subject Geographic: Lille; France
Description: International audience ; The use of the SWIR (Short Wave Infrared) spectrum, generally between 0.7 and 2.5 µm, has opened up new perspectives in the field of imaging, particularly in the development of autonomous vehicles (AVs). While current obstacle detection solutions demonstrate appreciable effectiveness under favourable weather conditions, there is still room for improvement to increase the safety of AVs in partially unknown road environments subject to difficult weather conditions (rain, snow, fog, glare, etc.), both day and night. This is the context of this study, with the integration of a SWIR camera into the sensory architecture of AVs.
Document Type: conference object; still image
Language: English
Availability: https://hal.science/hal-04871003; https://hal.science/hal-04871003v1/document; https://hal.science/hal-04871003v1/file/Poster_RFIAP___Alexandre_Riffard.pdf
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.6C517990
Database: BASE