Vision algorithms for fixed-wing unmanned aerial vehicle landing system | |
Alternative Title | Vision algorithms for fixed-wing unmanned aerial vehicle landing system |
Fan Yanming1; Ding Meng2; Cao Yunfeng2 | |
2017 | |
Source Publication | Science China. Technological Sciences
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ISSN | 1674-7321 |
Volume | 60Issue:3Pages:434-443 |
Abstract | 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. |
Other Abstract | 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. |
Keyword | vision-based landing spectral residual sparse coding position and pose estimation orthogonal iteration |
Indexed By | CSCD |
Language | 英语 |
CSCD ID | CSCD:5931676 |
Citation statistics |
Cited Times:3[CSCD]
[CSCD Record]
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Document Type | 期刊论文 |
Identifier | http://ir.imr.ac.cn/handle/321006/153265 |
Collection | 中国科学院金属研究所 |
Affiliation | 1.中国科学院金属研究所 2.南京航空航天大学 |
Recommended Citation GB/T 7714 | Fan Yanming,Ding Meng,Cao Yunfeng. Vision algorithms for fixed-wing unmanned aerial vehicle landing system[J]. Science China. Technological Sciences,2017,60(3):434-443. |
APA | Fan Yanming,Ding Meng,&Cao Yunfeng.(2017).Vision algorithms for fixed-wing unmanned aerial vehicle landing system.Science China. Technological Sciences,60(3),434-443. |
MLA | Fan Yanming,et al."Vision algorithms for fixed-wing unmanned aerial vehicle landing system".Science China. Technological Sciences 60.3(2017):434-443. |
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