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Method for detecting unmanned aerial vehicle visual navigation landing cooperative target robust

A cooperative target and visual navigation technology, applied in the field of navigation, can solve problems such as large-scale distortion of cooperative targets, undiscovered detection methods, etc., and achieve the effects of strong anti-interference ability, development prospects, engineering application value, and convenient implementation

Inactive Publication Date: 2015-04-29
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

Because the airborne camera is affected by the attitude of the aircraft, it is likely to cause large-scale distortion of the cooperative targets captured, and there will be many non-cooperative targets and other interference factors in the background, which has not been found in the current research results. Appropriate detection method

Method used

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  • Method for detecting unmanned aerial vehicle visual navigation landing cooperative target robust
  • Method for detecting unmanned aerial vehicle visual navigation landing cooperative target robust
  • Method for detecting unmanned aerial vehicle visual navigation landing cooperative target robust

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Embodiment Construction

[0034] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0035] The method of the present invention is further specifically described below, and the specific implementation steps of each part are as follows:

[0036] 1. Design of cooperation goals

[0037] The red square is used as the large backplane, the fluorescent green H and the small regular triangle are used as cooperation targets, and the small regular triangle is placed 45 degrees below the H shape.

[0038] 2. Image preprocessing

[0039] The image is preprocessed by threshold segmentation, median filter, erosion and dilation to separate the target and background. The threshold segmentation method adopts adaptive threshold segmentation, and the formula is as follows:

[0040] R(i,j)>90&&R(i,j)^2>2*(G(i,j)^2+B(i,j)^2) (1)

[0041] Among them, R(i, j), G(i, j) and B(i, j) are the red, green and blue components of the image respectively.

[0042] 3. Extract...

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Abstract

The invention relates to a method for detecting unmanned aerial vehicle visual navigation landing cooperative target robust, which is used for solving the problem that a cooperative target is difficult to detect accurately due to the large distortion of a cooperative target which is shot by an airborne camera and a plurality of non-cooperative targets in an image. A red square is designed to be a large back plate, fluorescent green H and small triangles are used as the cooperative targets, a corner point detection algorithm which combines a massively parallel processor (MPP) method and a Harris method is proposed to accurately detect the corner points of the cooperative targets under the condition of complicated environments and large distortion, and the method effectively combines the advantages of high detection precision of a Harris corner point and directionality of an MPP corner point. Compared with the conventional scheme for detecting an unmanned aerial vehicle visual navigation landing cooperative target, the method is not only easy to realize, but also can be used for effectively solving the problem of detecting the cooperative targets under the condition of complicated backgrounds and large distortion. The detection accuracy is improved, the engineering is conveniently realized, and the method has an important meaning to unmanned aerial vehicle independent safety landing.

Description

technical field [0001] The invention is a visual navigation technology oriented to engineering applications, which belongs to the field of navigation technology, and in particular relates to a robust detection method for a drone landing visual navigation cooperation target. Background technique [0002] Computer vision technology has been widely used in many fields due to its advantages of passive, autonomous and large amount of information. The airborne autonomous landing navigation method combined with vision sensor and other sensors has become a research hotspot in recent years. Many research institutions at home and abroad have carried out research on this work, such as the University of California at Berkeley, the University of Southern California, and the University of Florida in foreign countries, and the Western Polytechnic University, Beihang University, China Southern Airlines, and Tsinghua University in China. The detection of cooperative targets is the most crit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/00
Inventor 马旭程咏梅郝帅赵建涛王涛睢志佳孔若男宋林刘楠杜立一阮小明
Owner NORTHWESTERN POLYTECHNICAL UNIV
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