OV2SLAM: A Fully Online and Versatile Visual SLAM for Real-Time Applications
Type | Article | ||||||||||||
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Date | 2021-04 | ||||||||||||
Language | English | ||||||||||||
Author(s) | Ferrera Maxime![]() ![]() ![]() ![]() ![]() |
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Affiliation(s) | 1 : DTIS, ONERA, Université Paris-Saclay, Palaiseau, France 2 : IFREMER, Ctr. Méditerranée, Underwater System Unit, CS20330, La-Seyne-Sur-Mer, France |
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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 | 28 | ||||||||||||
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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