Research on Binocular Vision-Aided Inertial Navigation System

被引：0

作者：

Wu, Ping ^{[1
]}

Zhang, Hai ^{[1
]}

Du, RuiFeng ^{[1
]}

机构：

[1] Beihang Univ, Natl Key Lab Sci & Technol Integrated Control Tec, Beijing 100191, Peoples R China

来源：

PROCESSING OF 2014 INTERNATIONAL CONFERENCE ON MULTISENSOR FUSION AND INFORMATION INTEGRATION FOR INTELLIGENT SYSTEMS (MFI) | 2014年

关键词：

Vision-Aided; GPS-denied; SURF; Kalman Filter;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页数：6

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