Vision algorithms for fixed-wing unmanned aerial vehicle landing system

IMR OpenIR

	Vision algorithms for fixed-wing unmanned aerial vehicle landing system
其他题名	Vision algorithms for fixed-wing unmanned aerial vehicle landing system
	Fan Yanming 1; Ding Meng 2; Cao Yunfeng 2
	2017
发表期刊	Science China. Technological Sciences
ISSN	1674-7321
卷号	60 期号:3 页码:434-443
摘要	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.
其他摘要	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.
关键词	vision-based landing spectral residual sparse coding position and pose estimation orthogonal iteration
收录类别	CSCD
语种	英语
CSCD记录号	CSCD:5931676
引用统计	被引频次：4[CSCD] [CSCD记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/153265
专题	中国科学院金属研究所
作者单位	1.中国科学院金属研究所 2.南京航空航天大学
推荐引用方式 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.