Abstract
Subject matter: Research and development of methods for controlling swarms of unmanned aerial vehicles (UAVs) based on the "master – slave" model. This includes examining existing classifications and interactions between unmanned aerial vehicles in various formations such as groups, flocks, associations, and swarms, with the goal of creating an effective management system. Goal To improve the quality of interaction between unmanned aerial vehicles based on the "master – slave" model during flight missions through constant control between objects. Ensuring reliable execution of flight missions by implementing new management methods that account for different modes of interaction between devices. Tasks: Analyze the classification of existing UAVs; analyze the parameters and model of interaction of unmanned aerial vehicles in existing groups, flocks, associations, swarms; create a scenario of interaction between two UAVs based on the "master – slave" model; develop a program for visualizing the flight of unmanned aerial vehicles based on the "master – slave" model; conduct flight testing according to the proposed model on stages with various geospatial objects. Methods: Simulation method for developing a UAV flight visualization subsystem; graphical modeling method for creating an aircraft-type unmanned aerial vehicle model; methods of algorithm theory for developing a scenario of interaction between two UAVs. Utilization of specialized software tools for visualization and simulation of UAV behavior in real-time conditions. Results: Developed a classification of unmanned aerial vehicles; created a graphical model of the Mini-Flight-M aircraft; developed a scheme for the interaction of two UAVs in "teacher" or "mentor" modes; created a program for visualizing the flight of UAVs based on the "master – slave" model; conducted flight testing according to the proposed model on stages with various geospatial objects. The results confirmed the effectiveness of the developed model and demonstrated its applicability in various fields, including environmental monitoring, rescue operations, and other autonomous missions. Conclusions: The proposed approach to controlling a UAV swarm based on the "master – slave" model improves the quality of interaction between the devices and ensures reliable execution of flight missions. Further research should focus on optimizing energy consumption and ensuring reliable communication between swarm agents. It is also important to develop methods for protecting UAV swarms from cyberattacks and other threats to enhance their resilience and reliability during complex missions.
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