Abstract:
The article centers on the research objectives and tasks associated with
developing a swarm control system for unmanned aerial vehicles (UAVs)
utilizing artificial intelligence (AI). A comprehensive literature review was
undertaken to assess the effectiveness of the "swarm" method in UAV
management and identify key challenges in this domain. Swarm algorithms
were implemented in the MATLAB/Simulink environment for modeling and
simulation purposes. The study successfully instantiated and simulated a UAV
swarm control system adhering to fundamental principles and laws. Each
UAV operates autonomously, following target-swarm principles inspired by
the collective behavior of bees and ants. The collective movement and
behavior of the swarm are controlled by an AI-based program. The system
demonstrated effective obstacle detection and avoidance through computer
simulations. Results obtained highlight key features contributing to success,
including decentralized autonomy, collective intelligence, UAV coordination,
scalability, and flexibility. The deployment of a local radio communication
system in UAV swarm control and remote object monitoring is also discussed.
The research findings hold practical significance as they enable the effective
execution of complex tasks and have potential applications in various fields.
