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This paper explores the application of discrete-event systems (DES) and supervisory control theory for topological recovery of drone swarms. A hybrid architecture is proposed, integrating a high-level DES supervisor with a low-level continuous controller to enable safe recovery of lost drones. Simulations with ten UAVs in py-bullet-drones demonstrate the method's effectiveness across various scenarios, including a secondary supervisor for regrouping after recovery.
Guaranteeing swarm drone recovery from faults is now possible with a hybrid discrete-event system that merges high-level supervision with low-level control.
Discrete-event systems and supervisory control theory provide a rigorous framework for specifying correct-by-construction behavior. However, their practical application to swarm robotics remains largely underexplored. In this paper, we investigate a topological recovery method based on discrete-event-systems within a swarm robotics context. We propose a hybrid architecture that combines a high-level discrete event systems supervisor with a low-level continuous controller, allowing lost drones to safely recover from fault or attack events and re-enter a controlled region. The method is demonstrated using ten simulated UAVs in the py-bullet-drones framework. We show recovery performance across four distinct scenarios, each with varying initial state estimates. Additionally, we introduce a secondary recovery supervisor that manages the regrouping process for a drone after it has re-entered the operational region.
