用离散事件系统让无人机群在故障后自动安全回归控制区域
A Case Study in Recovery of Drones using Discrete-Event Systems
- 高低层协同：高层用离散事件系统监督，低层用连续控制器执行
- 10架模拟无人机在4种初始状态下发射后均成功恢复
- 适合研究无人机集群容错与自主恢复的学者和工程师
离散事件系统与监督控制理论为构建正确性可保证的行为提供了严谨框架，但其在群体机器人中的实际应用仍较少。本文研究了一种基于离散事件系统的拓扑恢复方法，应用于群体机器人场景。提出一种混合架构，结合高层离散事件系统监督器与底层连续控制器，使丢失的无人机能安全应对故障或攻击事件，并重新进入受控区域。在py-bullet-drones框架中使用十架模拟无人机进行验证，展示了四种不同初始状态估计下的恢复性能。此外，引入次级恢复监督器，管理无人机重返工作区域后的重新集结过程。
原文摘要 · Abstract (English)
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.
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