Metric, dense and real-time 3D Reconstruction for drone autonomous navigation - Archive ouverte HAL
Poster De Conférence Année : 2021

Metric, dense and real-time 3D Reconstruction for drone autonomous navigation

Reconstruction 3D dense, métrique et temps réel pour la navigation autonome de drone

Résumé

Simultaneous Localization And Mapping (SLAM) research have reach maturity allowing state of the art algorithm to build a 3D dense and metric reconstruction in real-time. However, it becomes more challenging in drone navigation context where we favor passive sensors in monocular configuration and need to tackle fast motions or illumination changes. Research on Deep learning monocular depth estimation and event cameras present interesting advances to resolve these challenges.
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Dates et versions

hal-03573685 , version 1 (14-02-2022)

Identifiants

  • HAL Id : hal-03573685 , version 1

Citer

Yassine Habib, Panagiotis Papadakis, Cédric Le Barz, Cédric Buche, Antoine Fagette. Metric, dense and real-time 3D Reconstruction for drone autonomous navigation. Journée des Jeunes Chercheurs en Robotique (JJCR 2021), Oct 2021, Paris, France. , 2021. ⟨hal-03573685⟩

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