期刊
IEEE TRANSACTIONS ON ROBOTICS
卷 31, 期 5, 页码 1147-1163出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2015.2463671
关键词
Lifelong mapping; localization; monocular vision; recognition; simultaneous localization and mapping (SLAM)
类别
资金
- Direccion General de Investigacion of Spain [DPI2012-32168]
- Ministerio de Educacion Scholarship [FPU13/04175]
- Gobierno de Aragon Scholarship [B121/13]
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.
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