Issue 1 (215), article 2

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DOI:

Cybernetics and Computer Engineering, 2024,1(215)

Dzhebrailov R.Yu., PhD Student,
Junior Researcher of the Research Laboratory of Unmanned Complexes and Systems,
https://orcid.org/0000-0002-4473-9670,
e-mail: rombik1197@gmail.com

Gospodarchuk O.Yu.,
Senior Researcher of the Intelligent Control Department
https://orcid.org/0000-0001-6619-2277,
e-mail: olexago@gmail.com

International Research and Training Center
for Information Technologies and Systems
of the National Academy of Science of Ukraine
and the Ministry of Education and Science of Ukraine.
40, Acad. Glushkov av., 03187, Kyiv, Ukraine

DETECTION OF SPECIAL ZONES AS A BASIS FOR THE METHOD OF TOPOGRAPHIC AFFINITY OF IMAGES

Introduction. The satellite and inertial navigation systems of an unmanned aerial vehicle (UAV) or unmanned aircraft system (UAS) have their drawbacks. Attempts to eliminate these shortcomings are to develop an autonomous navigation system. The officially patented model of an autonomous navigation system, as it turned out, also has its drawbacks. Accordingly, there is a need to improve such an autonomous navigation system.

The purpose of the paper is to develop and study a method for determining the topographic affinity of images based on the detected special zones in images of the natural landscape for autonomous UAV navigation.

Results. A method of topographic affinity of visual images based on the detection of special zones by searching for local maxima of the Laplace operator in the image has been developed. The method of topographic affinity of images allows  involving a smaller number of special points for comparison, which reduces the amount of required memory resources and increases performance.

Conclusions. The proposed method of topographic affinity of images based on the detection of special zones (blob detection methods) based on the principle of searching for local maxima of the Laplace operator can be used to build an autonomous navigation system for UAVs. The algorithmic implementation of the method has shown that it can work with a large number of complex and diverse images of the earth’s surface obtained during UAV flights, is effective by increasing the processing speed of the studied images, and can be implemented to create full-fledged UAV autonomous navigation systems.

Keywords: unmanned aerial vehicle, unmanned aerial vehicle complex, autonomous navigation, special points, special zones, method of special image zones analysis.

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Received 19.12.2023