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Vision algorithms for fixed-wing unmanned aerial vehicle landing system

查看参考文献21篇

Fan Yanming 1 *   Ding Meng 2   Cao Yunfeng 3  
文摘 Autonomous landing has become a core technology of unmanned aerial vehicle (UAV) guidance, navigation and control system in recent years. As a novel autonomous landing approach, computer vision has been studied and applied in rotary-wing UAV landing successfully. This paper aims to fixed-wing UAV and focus on two problems: how to find runway only depending on airborne front-looking camera and how to align UAV with the designated landing runway. The paper can be divided into two parts to solve above two problems respectively. In the first part, the paper firstly presents an algorithm of region of interest (ROI) detection, which is based on spectral residual saliency map, and then an algorithm of feature vector extraction based on sparse coding and spatial pyramid matching (SPM) is proposed, finally, ROI including designated landing runway is recognized by a linear support vector machine. In the second part, the paper presents an approach of relative position and pose estimation between UAV and landing runway. Estimation algorithm firstly selects five feature points on the runway surface, and then establishes a new earth-fixed reference frame, finally uses orthogonal iteration to estimate landing parameters including three parameters of distance, height and offset, and three pose parameters of roll, yaw, pitch. The experimental results verify the effectiveness of the algorithms proposed in this paper.
来源 Science China. Technological Sciences ,2017,60(3):434-443 【核心库】
DOI 10.1007/s11431-016-0618-3
关键词 vision-based landing ; spectral residual ; sparse coding ; position and pose estimation ; orthogonal iteration
地址

1. Shenyang Aircraft Design & Research Institute, Aviation Industry Corporation of China, Shenyang, 110035  

2. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106  

3. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016

语种 英文
文献类型 研究性论文
ISSN 1674-7321
学科 航空
文献收藏号 CSCD:5931676

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