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
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 .

Full Text
File Pages Size Access
8 1 MB Access on demand
Author's final draft 12 1 MB Open access
Top of the page