Quad-rotor unmanned aerial vehicle autonomous landing method based on visual positioning

A UAV, sign technology, applied in medical rescue, machine learning and image processing, power inspection, environmental monitoring, disaster monitoring and agricultural perception fields, can solve the problem that the accuracy of UAV positioning and attitude calculation needs to be improved, external The complexity of the environment, the problem that the image feature information of the pose solution cannot be well utilized, etc.

CN110569838AActive Publication Date: 2019-12-13INNER MONGOLIA UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2019-12-13

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Abstract

The invention discloses a quad-rotor unmanned aerial vehicle autonomous landing method based on visual positioning. In order to enable the quad-rotor unmanned aerial vehicle to autonomously and accurately land on a ground landing platform so as to carry out fixed protection, charging endurance and mobile carrying on the quad-rotor unmanned aerial vehicle, a visual identification mark composed of aregular triangle and concentric rings is designed, and a novel vision-based quad-rotor unmanned aerial vehicle autonomous landing method is provided based on the identification mark. In the first stage of the method, position parameters of an unmanned aerial vehicle and the center of an identification mark are calculated through a regular triangle of the identification mark; in the second stage,the position deviation and the yaw angle between the unmanned aerial vehicle and the center of the identification mark are determined through concentric rings and heading reference lines in the concentric rings, and finally attitude adjustment and autonomous landing of the unmanned aerial vehicle are completed. Through verification of a landing experiment of the unmanned aerial vehicle, the methodcan accurately extract sign features, calculate position information and angle information of the unmanned aerial vehicle relative to the identification sign in real time, and realize accurate landing.
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Description

technical field

[0001] The invention is applied to the fields of electric power inspection, medical rescue, environmental monitoring, disaster monitoring, agricultural perception and the like. In these applications, the key technology is the autonomous landing of the UAV. To realize the autonomous landing of the UAV, the first solution is the sign detection and attitude estimation. A man-machine autonomous landing method belongs to the technical field of machine learning and image processing. Background technique

[0002] With the vigorous development of intelligent technology, microelectronics technology, digital communication technology, sensing technology and virtual reality technology, quadrotor UAVs have been vigorously developed in both military and civilian fields. The quadrotor UAV involves many aspects of knowledge such as navigation, computer vision, control theory, embedded electronics, etc. It has the characteristics of small size, low cost, flexible maneuverabi...

Examples

Embodiment Construction

[0091] In order to verify the validity and accuracy of the segmented control algorithm for autonomous landing of the UAV proposed by the present invention, a quadrotor UAV is used to simulate its landing process to collect image data, and then the image data is input into the algorithm of the present invention, and the output of the algorithm is compared by comparing the image data. The error between the estimated value and the measured true value validates the algorithm. In addition, the time performance of the algorithm proposed in the present invention is also compared and analyzed.

[0092] 1. Experimental platform and parameter selection

[0093] The algorithm running environment is a laptop, the hardware configuration is Intel(R) Core i5 processor, 3.20GHz main frequency, 8.0GB memory, 64-bit Windows7 flagship operating system is installed; the software uses Visual Studio2015, based on the open source computer vision library (OpenCV), using C++ language programming to a...