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所属单位：航天学院

发表刊物：PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING

关键字：Unmanned aerial vehicle vision-based navigation spectral residual locality-constraint linear coding linear support vector machine orthogonal iteration

摘要：Autonomous carrier landing is regarded as a crucial problem among the flight stages of carrier-based unmanned aerial vehicle. In recent years, vision-based guidance has become a promising solution for unmanned aerial vehicle autonomous carrier landing. In this paper a new vision-based navigation scheme is proposed for unmanned aerial vehicle autonomous carrier landing. The scheme aims at dealing with two core problems: searching the carrier by using the images obtained from the airborne forward-looking camera and estimating the relative position and attitude between the unmanned aerial vehicle and the carrier. In order to solve the first problem, the spectral residual-based saliency analysis method is firstly adopted to obtain the Region of Interest. Then the locality-constraint linear coding-based feature learning method is proposed for feature extraction, and the region of interest containing the carrier is finally recognized by the linear support vector machine. In order to solve the second problem, five feature points are firstly selected on the surface of the carrier. Then, a new carrier-fixed moving reference coordinate system is set up. The six landing parameters including three attitude parameters and three position parameters are finally obtained by using orthogonal iteration. The experiment results verify the superiority and effectiveness of the algorithms proposed in this paper.

ISSN号：0954-4100

是否译文：否

发表时间：2019-06-01

合写作者：Zhang, Zhouyu,丁萌,庄丽葵,Tao, Jiang

通讯作者：曹云峰