Analysis of autonomous navigation methods for drone swarms: centralized and decentralized approaches

Abstract

The work is dedicated to a comprehensive comparative analysis of autonomous navigation methods for swarms of unmanned aerial vehicles. It examines the conceptual differences, technical advantages, and critical disadvantages of centralized and decentralized control approaches in complex environments. Based on aggregated data, key algorithmic foundations (Swarm Intelligence, APF), issues of scalability, fault tolerance, the impact of communication interference, and cybersecurity threats are analyzed. Prospects for the use of adaptive hybrid architectures and Edge Computing to enhance the overall efficiency and autonomy of the swarm are presented. The results of the analysis can be used for the informed selection of swarm control architecture when designing systems for civilian and military applications.