Multi-criteria Knowledge-based decision-making functionality for swarm of drones

Unmanned Aerial Vehicles (UAVs), or commonly referred to as drones are now being utilized for a variety of data-intensive applications in the transportation civil and military sectors, in a way that has never occurred before. The UAV swarm system, which refers to a cooperative formation of UAVs that conduct exploration and mapping activities in a synergistic mode, is part of the most well-known new scenarios that have been introduced in recent years. A significant challenge of such systems is determining the kind of UAV swarm architecture that will enable increased efficiency and resilience in operations. This study suggests a framework for energy efficient and robust swarm missions that relies on a decision-based functionality for the actions of each entity in the swarm for various mission scenarios, while numerical results showcase the efficiency of our proposed method. Finally, comprehensive simulation results based on a custom-developed simulator showcase the effectiveness, scalability, and applicability of the proposed model.