
ДОСЛІДЖЕННЯ АЛГОРИТМІВ НАВІГАЦІЇ ТА КАРТОГРАФІЇ ДЛЯ БЕЗПІЛОТНОГО ЛІТАЛЬНОГО АПАРАТУ
Author(s) -
Ю. М. Толкунова,
Д. О. Подколзіна
Publication year - 2021
Publication title -
otkrytye informacionnye i kompʹûternye integrirovannye tehnologii
Language(s) - English
Resource type - Journals
eISSN - 2663-2411
pISSN - 2071-1077
DOI - 10.32620/oikit.2021.91.12
Subject(s) - visual odometry , computer science , computer vision , artificial intelligence , task (project management) , focus (optics) , simultaneous localization and mapping , odometry , navigation system , operator (biology) , robot , mobile robot , engineering , physics , systems engineering , optics , biochemistry , chemistry , repressor , transcription factor , gene
The methods of navigation of an unmanned aerial vehicle (UAV) are considered. The main focus is on navigation methods that reduce the operator's activities to setting the current task and monitoring the operation of the UAV. The UAV must independently assess the environment and plan its path, including in the presence of other moving objects. The solution of control and navigation tasks for UAVs without a remote control significantly facilitates the operator's task, but requires the development of a UAV control system. These tasks include the task of automatically returning the UAV in case of loss of communication with the operator, the solution of which increases the reliability of the navigation system. The change in the nature of the operator's activity, who now does not directly control the movements of the UAV, leads to a change in the nature of the control system. One of the ways to solve this problem is to use an optical navigation system. The analysis of methods and algorithms for optical navigation of an unmanned aerial vehicle: algorithms for local navigation and cartography, correlation-extreme navigation methods and methods of visual odometry. The advantages and disadvantages of optical navigation methods are considered. The use of visual odometry methods has advantages over other methods, but it also has disadvantages associated with the accumulation of errors in the course of the method. Variations of algorithms for simultaneous localization and mapping (SLAM) based on the use of cameras are called visual SLAM. The visual SLAM and visual odometry methods are analyzed. Hybrid SLAM methods solve the problem of error accumulation.The use of UAVs for studying geological processes of the coastline of reservoirs and seas is analyzed. The advantages of using SLAM algorithms for monitoring the state of the coastline are considered. It is concluded that the use of SLAM algorithms for assessing the density of the erosion network of the coastline of reservoirs and seas makes it possible to obtain images without geometric distortions, an optical navigation system based on these algorithms greatly facilitates the operator's task, and will allow the UAV to be returned in case of loss of communication with the operator.