From sparse SLAM to dense mapping for UAV autonomous navigation

Yassine Habib; Panagiotis Papadakis; Antoine Fagette; Cédric Le Barz; Tiago Gonçalves; Cédric Buche

doi:10.1117/12.2663706

15 June 2023 From sparse SLAM to dense mapping for UAV autonomous navigation

Yassine Habib, Panagiotis Papadakis, Antoine Fagette, Cédric Le Barz, Tiago Gonçalves, Cédric Buche

Proceedings Volume 12525, Geospatial Informatics XIII ; 125250C (2023) https://doi.org/10.1117/12.2663706
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Autonomous or semi-autonomous navigation of UAVs is of great interest in the Defense and Security domains, as it significantly improves their efficiency and responsiveness during operations. The perception of the environment and in particular the dense and metric 3D mapping in real time is a priority for navigation and obstacle avoidance. We therefore present our strategy to jointly estimate a dense 3D map by combining a sparse map estimated by a state-of-the-art Simultaneous Localization and Mapping (SLAM) system and a dense depth map predicted by a monocular self-supervised method. Then, a lightweight and volumetric multi-view fusion solution is used to build and update a voxel map.

Conference Presentation

Citation Download Citation

Yassine Habib, Panagiotis Papadakis, Antoine Fagette, Cédric Le Barz, Tiago Gonçalves, and Cédric Buche "From sparse SLAM to dense mapping for UAV autonomous navigation", Proc. SPIE 12525, Geospatial Informatics XIII , 125250C (15 June 2023); https://doi.org/10.1117/12.2663706

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