A Case Study in Recovery of Drones using Discrete-Event Systems
Liam P. Burns, Dayse M. Cavalcanti, Felipe G. Cabral, Max H. de Queiroz, Melissa Greeff, Publio M. M. Lima, Karen Rudie
- Year
- 2026
- Access
- Open access
Abstract
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.
Keywords
Related papers
Hierarchical decision-making for UAVs’ game via LLM enhanced multi-agent reinforcement learning
Xinyu Dong, Bo Li, Guangyu Zhang +2 more
Aerospace Science and Technology · 2026
Dynamic reconfiguration in multi-robot agent systems using embedded language models
Shokhikha Amalana Murdivien, Jongsu Park, Jumyung Um
Robotics and Computer-Integrated Manufacturing · 2026
Formation optimization and obstacle avoidance decision-making methods for cooperative coverage search of multi-UUVs in underwater wreck areas
Haomiao Yu, Zeyuan Zhang, Yantian Ma
Robotics and Autonomous Systems · 2026
Human-in-the-Loop Swarms: A Bionic Swarm Approach to Real-World Soil Mapping
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu +3 more
2026