A Case Study in Recovery of Drones using Discrete-Event Systems

TL;DR

This paper explores a topological recovery method for swarm robotics using discrete-event systems, demonstrating how UAVs can recover from faults and attacks through a hybrid control architecture.

Contribution

It introduces a novel hybrid architecture combining high-level discrete-event supervisors with low-level controllers for drone recovery in swarm robotics.

Findings

Recovery performance varies across different initial state estimates.

The secondary supervisor effectively manages drone regrouping.

Simulations validate the proposed recovery approach.

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.