TY - JOUR T1 - OV2SLAM: A Fully Online and Versatile Visual SLAM for Real-Time Applications A1 - Ferrera,Maxime A1 - Eudes,Alexandre A1 - Moras,Julien A1 - Sanfourche,Martial A1 - Le Besnerais,Guy AD - DTIS, ONERA, Université Paris-Saclay, Palaiseau, France AD - IFREMER, Ctr. Méditerranée, Underwater System Unit, CS20330, La-Seyne-Sur-Mer, France UR - https://doi.org/10.1109/LRA.2021.3058069 DO - 10.1109/LRA.2021.3058069 KW - SLAM KW - localization KW - mapping KW - field robotics N2 - 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 . Y1 - 2021/04 PB - Institute of Electrical and Electronics Engineers (IEEE) JF - Ieee Robotics And Automation Letters SN - 2377-3766 VL - 6 IS - 2 SP - 1399 EP - 1406 ID - 79583 ER -