|Author(s)||Ferrera Maxime1, 2, Eudes Alexandre1, Moras Julien1, Sanfourche Martial1, Le Besnerais Guy1|
|Affiliation(s)||1 : DTIS, ONERA, Université Paris-Saclay, Palaiseau, France
2 : IFREMER, Ctr. Méditerranée, Underwater System Unit, CS20330, La-Seyne-Sur-Mer, France
|Source||Ieee Robotics And Automation Letters (2377-3766) (Institute of Electrical and Electronics Engineers (IEEE)), 2021-04 , Vol. 6 , N. 2 , P. 1399-1406|
|WOS© Times Cited||28|
|Keyword(s)||SLAM, localization, mapping, field robotics|
Many applications of Visual SLAM, such as augmented reality, virtual reality, robotics or autonomous driving, require versatile, robust and precise solutions, most often with real-time capability. In this work, we describe OV 2 SLAM, a fully online algorithm, handling both monocular and stereo camera setups, various map scales and frame-rates ranging from a few Hertz up to several hundreds. It combines numerous recent contributions in visual localization within an efficient multi-threaded architecture. Extensive comparisons with competing algorithms shows the state-of-the-art accuracy and real-time performance of the resulting algorithm. For the benefit of the community, we release the source code: https://github.com/ov2slam/ov2slam .
Ferrera Maxime, Eudes Alexandre, Moras Julien, Sanfourche Martial, Le Besnerais Guy (2021). OV2SLAM: A Fully Online and Versatile Visual SLAM for Real-Time Applications. Ieee Robotics And Automation Letters, 6(2), 1399-1406. Publisher's official version : https://doi.org/10.1109/LRA.2021.3058069 , Open Access version : https://archimer.ifremer.fr/doc/00684/79583/