In the research community, there’s a keen interest in the challenges faced when drones are deployed for tasks like surveillance, environmental monitoring, and search-and-rescue operations. Fundamental behaviors such as coverage control and area monitoring are crucial for dynamic missions. This paper introduces the results of a control algorithm for monitoring points of interest within the context of drone deployment. The goal is not only to present a novel approach based on Voronoi diagrams and Control Barrier Functions but also to demonstrate the algorithm’s ability to maintain formation and complete tasks in scenarios where the drone swarm encounters obstacles in an environment whose map is unknown a priori. To validate the effectiveness of our approach, we conducted an experimental study featuring a comprehensive suite of simulations, where the working conditions and potential environmental obstacles were not known in advance.
Dual-Layer Control Architecture for Cooperative Environmental Monitoring in Multi-robot Systems / Catellani, M.; Belal, M.; Sabattini, L.. - 34:(2026), pp. 15-27. ( 17th International Symposium on Distributed Autonomous Robotic Systems, DARS 2024 usa 2024) [10.1007/978-3-032-04584-3_2].
Dual-Layer Control Architecture for Cooperative Environmental Monitoring in Multi-robot Systems
Catellani M.
;Belal M.;Sabattini L.
2026
Abstract
In the research community, there’s a keen interest in the challenges faced when drones are deployed for tasks like surveillance, environmental monitoring, and search-and-rescue operations. Fundamental behaviors such as coverage control and area monitoring are crucial for dynamic missions. This paper introduces the results of a control algorithm for monitoring points of interest within the context of drone deployment. The goal is not only to present a novel approach based on Voronoi diagrams and Control Barrier Functions but also to demonstrate the algorithm’s ability to maintain formation and complete tasks in scenarios where the drone swarm encounters obstacles in an environment whose map is unknown a priori. To validate the effectiveness of our approach, we conducted an experimental study featuring a comprehensive suite of simulations, where the working conditions and potential environmental obstacles were not known in advance.| File | Dimensione | Formato | |
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