OV2SLAM: A Fully Online and Versatile Visual SLAM for Real-Time Applications

Type Article
Date 2021-04
Language English
Author(s) Ferrera MaximeORCID1, 2, Eudes AlexandreORCID1, Moras JulienORCID1, Sanfourche MartialORCID1, Le Besnerais GuyORCID1
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
DOI 10.1109/LRA.2021.3058069
WOS© Times Cited 1
Keyword(s) SLAM, localization, mapping, field robotics
Abstract

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 .

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