空中ロボットによる持続的監視と目標検出：実環境での展開と評価
Aerial Robots Persistent Monitoring and Target Detection: Deployment and Assessment in the Field
複数の空中ロボットが協調して持続的に監視と目標検出を行う分散アルゴリズムを提案し、最大11機での実証実験で有効性と耐障害性を示した。
著者: Manuel Boldrer, Vit Kratky, Martin Saska
分類: cs.RO
原文アブストラクト
In this article, we present a distributed algorithm for multi-robot persistent monitoring and target detection. In particular, we propose a novel solution that effectively integrates the Time-inverted Kuramoto model, three-dimensional Lissajous curves, and Model Predictive Control. We focus on the implementation of this algorithm on aerial robots, addressing the practical challenges involved in deploying our approach under real-world conditions. Our method ensures an effective and robust solution that maintains operational efficiency even in the presence of what we define as type I and type II failures. Type I failures refer to short-time disruptions, such as tracking errors and communication delays, while type II failures account for long-time disruptions, including malicious attacks, severe communication failures, and battery depletion. Our approach guarantees persistent monitoring and target detection despite these challenges. Furthermore, we validate our method with extensive field experiments involving up to eleven aerial robots, demonstrating the effectiveness, resilience, and scalability of our solution.
