Coverage Optimization with Connectivity Preservation for UAV Swarms Applying Chaotic Dynamics

Martin Rosalie (1) , Matthias R Brust (1) , Grégoire Danoy (2) , Serge Chaumette (3) , Pascal Bouvry (2)

1 SnT - Interdisciplinary Centre for Security, Reliability and Trust [Luxembourg]
2 CSC - Computer Science and Communications Research Unit [Luxembourg]
3 LaBRI - Laboratoire Bordelais de Recherche en Informatique

Cooperative usage of multiple UAVs as a swarm can deliver high-quality surveillance performance. However, the communication capabilities within the UAV swarm must be maintained for local data propagation to swarm members in favor of achieving an efficient global behavior. In this paper, we address the problem of optimizing two adversary criteria for such a UAV swarm: (a) maximizing the area coverage, while (b) preserving network connectivity. Our approach, called CACOC² , solves the problem with a novel chaotic ant colony optimization approach, which combines an Ant Colony Optimization approach (ACO) with a chaotic dynamical system. CACOC² employs swarming behavior to obtain UAV clustering that result in maximized area coverage and preserved network connectivity. We show by extensive simulations how the size of the UAV swarm influences the coverage and connectivity. A metrics comparison chart shows the correlation of coverage and connectivity metrics.

Mots clés: cooperative UAV; multilevel swarm; mobility model; ant colony optimization; chaotic dynamics

Domaines: Système multi-agents [cs.MA]; Dynamique Chaotique [nlin.CD]; Systèmes dynamiques [math.DS]

Martin Rosalie, Matthias R Brust, Grégoire Danoy, Serge Chaumette, Pascal Bouvry. Coverage Optimization with Connectivity Preservation for UAV Swarms Applying Chaotic Dynamics. 2017 IEEE International Conference on Autonomic Computing (ICAC), Jul 2017, Columbus, United States. pp.113-118, ⟨10.1109/ICAC.2017.26⟩. ⟨hal-01574636⟩