StructVIO: Visual-Inertial Odometry With Structural Regularity of Man-Made Environments

• Published in: IEEE transactions on robotics Vol. 35; no. 4; pp. 999 - 1013
• Main Authors: Zou, Danping, Wu, Yuanxin, Pei, Ling, Ling, Haibin, Yu, Wenxian
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Atlanta world; Benchmark testing; Cameras; Feature extraction; inertial navigation; Odometers; Regularity; Simultaneous localization and mapping; structural lines; visual simultaneous localization and mapping (SLAM); visual-inertial odometry (VIO); Visualization; Atlanta Georgia
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2019.2915140

In this paper, we propose a novel visual-inertial odometry (VIO) approach that adopts structural regularity in man-made environments. Instead of using Manhattan world assumption, we use Atlanta world model to describe such regularity. An Atlanta world is a world that contains multiple local Manhattan worlds with different heading directions. Each local Manhattan world is detected on the fly, and their headings are gradually refined by the state estimator when new observations are received. With full exploration of structural lines that aligned with each local Manhattan worlds, our VIO method becomes more accurate and robust, as well as more flexible to different kinds of complex man-made environments. Through benchmark tests and real-world tests, the results show that the proposed approach outperforms existing visual-inertial systems in large-scale man-made environments.