Integrating Artificial Intelligence and Information Technologies in Autonomous UAV Navigation Systems

Oleksandr Kukla; Oksana Danylko; Stanislav Khlevytskyi; Dmytro Zienov; Kostiantyn Surkov

Authors

Oleksandr Kukla Department of Flight Operations and Flight Safety, Flight Operations Faculty, Ukrainian State Flight Academy, Kropyvnytskyi, Ukraine
Oksana Danylko Department of Information Technologies and Aviation Robotic Systems, Aviation Management Faculty, Ukrainian State Flight Academy, Kropyvnytskyi, Ukraine
Stanislav Khlevytskyi Department of Flight Operations and Flight Safety, Flight Operations Faculty, Ukrainian State Flight Academy, Kropyvnytskyi, Ukraine
Dmytro Zienov Department of Flight Operations and Flight Safety, Flight Operations Faculty, Ukrainian State Flight Academy, Kropyvnytskyi, Ukraine
Kostiantyn Surkov Department of Information Technology, Faculty of Economics, Robert Elvorti Economics and Technology Institute, Kropyvnytskyi, Ukraine

Keywords:

Unmanned aerial vehicles (UAVs), autonomous navigation, inertial navigation, artificial intelligence, adaptive algorithms, embedded programming, databases, cloud management, UAV cybersecurity, drone swarm

Abstract

The purpose of the research is to analyze modern information technologies and artificial intelligence algorithms used in autonomous navigation systems of unmanned aerial vehicles, as well as to determine their role in increasing the efficiency of navigation control in difficult flight conditions. The research was conducted in 2024–2025 based on the analysis of technical documentation of autonomous navigation algorithms, engineering specifications of flight control systems, open navigation data sets and simulation environments used in robotic systems. The results of the research showed that 34 of the 42 analyzed systems use a multi-level navigation architecture, while 38 systems integrate inertial sensors, 31 use satellite navigation modules, and 29 employ computer vision systems. The results obtained indicate that the integration of sensor systems, machine learning algorithms, and software platforms forms the technological basis for the development of autonomous control systems for unmanned aerial vehicles and creates the prerequisites for further improvement of navigation technologies in robotic systems.