Adaptive Real-Time Simulation and Autonomous Role Reconfiguration for Decentralized Unmanned Aerial Vehicle Swarm Coordination

Abstract This work introduces an adaptive decentralized coordination framework for unmanned aerial vehicle swarms that integrates real-time behavioral simulation, autonomous correction mechanisms, and dynamic role reconfiguration. The system maintains a continuously synchronized “shadow” simulation environment that mirrors live unmanned aerial vehicle telemetry, enabling early detection of positional drift, mission inconsistencies, and algorithmic deviations. Upon detecting abnormal behavior, the framework automatically dispatches corrective actions to preserve formation integrity and mission continuity. Additionally, a context-aware role management module allows unmanned aerial vehicles to dynamically switch between operational functions, such as reconnaissance, rescue, and attack, based on environmental triggers and task priorities. Built on a modular microservice architecture, the platform supports premission testing, in-flight coordination, and postmission analytics. The combination of deterministic traversal algorithms and adaptive autonomy enhances swarm robustness, scalability, and performance in constrained or communication-limited environments.