ORB-SLAM: A Versatile and Accurate Monocular SLAM System
ORB-SLAM: A Versatile and Accurate Monocular SLAM System
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DOI：
10.1109/tro.2015.2463671
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发表时间：
2015-10-01
影响因子：
7.8
通讯作者：
Tardos, Juan D.
中科院分区：
文献类型：
--
作者：
Mur-Artal, Raul;Montiel, J. M. M.;Tardos, Juan D.
本文介绍了一种基于特征的单目同步定位与制图（SLAM）系统，该系统可在小型和大型室内和室外环境中实时运行。该系统对严重的运动杂波具有鲁棒性，允许宽基线环路关闭和重新定位，并包括全自动初始化。基于近年来的优秀算法，我们从零开始设计了一个新颖的系统，该系统对所有SLAM任务使用相同的功能：跟踪，映射，重新定位和循环关闭。选择重建点和关键帧的适者生存策略具有出色的鲁棒性，并生成紧凑且可跟踪的地图，该地图仅在场景内容变化时才会增长，从而允许终身运行。我们提出了一个详尽的评估27序列从最流行的数据集。ORB-SLAM相对于其他最先进的单眼SLAM方法实现了前所未有的性能。为了社区的利益，我们将源代码公开。
This paper presents ORB-SLAM, a feature-based monocular simultaneous localization and mapping (SLAM) system that operates in real time, in small and large indoor and outdoor environments. The system is robust to severe motion clutter, allows wide baseline loop closing and relocalization, and includes full automatic initialization. Building on excellent algorithms of recent years, we designed from scratch a novel system that uses the same features for all SLAM tasks: tracking, mapping, relocalization, and loop closing. A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation. We present an exhaustive evaluation in 27 sequences from the most popular datasets. ORB-SLAM achieves unprecedented performance with respect to other state-of-the-art monocular SLAM approaches. For the benefit of the community, we make the source code public.