@inproceedings{3c52f045248e48c0aa4b39a34f157678,
title = "Research on binocular vision-aided inertial navigation system",
abstract = "This paper presents a vision-aided method to restrain INS from drifting in GPS-denied periods. This system is composed of two cameras and an inertial measurement unit. Contrary to traditional SLAM, the coordinates of the feature points or any other priori information are not indispensable in this method. By using the tracked feature point from two consecutive frames, incremental displacement and velocity can be computed as the measurements of navigation Kalman Filter. A dynamic indoor vision/INS experiment, which can significantly improve the performance of the navigation is included. In addition, the proposed method makes it possible to navigate in real time.",
keywords = "GPS-denied, Kalman Filter, SURF, Vision-Aided",
author = "Ping Wu and Hai Zhang and Ruifeng Du",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014 ; Conference date: 28-09-2014 Through 30-09-2014",
year = "2014",
month = dec,
day = "23",
doi = "10.1109/MFI.2014.6997753",
language = "英语",
series = "Proceedings of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014",
address = "美国",
}