OV2SLAM: A Fully Online and Versatile Visual SLAM for Real-Time Applications
OV2SLAM: A Fully Online and Versatile Visual SLAM for Real-Time Applications
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DOI：
10.1109/lra.2021.3058069
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发表时间：
2021-04-01
影响因子：
5.2
通讯作者：
Le Besnerais, Guy
中科院分区：
文献类型：
--
作者：
Ferrera, Maxime;Eudes, Alexandre;Le Besnerais, Guy
Visual SLAM的许多应用，如增强现实、虚拟现实、机器人或自动驾驶，都需要多功能、强大和精确的解决方案，而且通常都具有实时功能。在这项工作中，我们描述了OV（2）SLAM，一个完全在线的算法，处理单眼和立体相机设置，各种地图比例和帧速率范围从几赫兹到几百赫兹。它结合了视觉定位在一个高效的多线程架构的许多最新的贡献。与竞争算法的广泛比较显示了最先进的准确性和实时性能的算法。为了社区的利益，我们发布源代码：https://github.com/ov2slam/ov2slam。
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.