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

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 .


SLAM, localization, mapping, field robotics

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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. https://doi.org/10.1109/LRA.2021.3058069, https://archimer.ifremer.fr/doc/00684/79583/

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