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.

翻译：离散事件系统和监督控制理论为指定正确性构建行为提供了严谨的框架。然而，它们在实际集群机器人中的应用仍远未得到充分探索。本文在集群机器人背景下研究了一种基于离散事件系统的拓扑恢复方法。我们提出了一种混合架构，将高层离散事件系统监督器与低层连续控制器相结合，使丢失的无人机能够从故障或攻击事件中安全恢复并重新进入受控区域。该方法在py-bullet-drones框架中通过十架模拟无人机进行了演示。我们展示了四种不同情景下的恢复性能，每种情景具有不同的初始状态估计。此外，我们引入了一个次级恢复监督器，用于管理无人机重新进入运行区域后的重组过程。