Intelligent-Geometric Control Architecture for Extinguishing Fires by a Group of UAVs

Хачумов, М. В.; Khachumov, Vyacheslav

doi:10.1007/978-3-031-23609-9_20

Cited by 2 publications

(1 citation statement)

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“…As technological advancements continue and application scenarios broaden, the distinctive value of UAV swarm cooperative networks is anticipated to be increasingly prominent across diverse fields. A pivotal challenge, however, is the effective management and control of these UAV swarms to maximize collaborative effects, particularly in real-time coordination within expansive, dynamic environments [6][7][8][9]. Consequently, the formulation of an efficient distributed computing optimization strategy has become imperative.…”

Section: Introductionmentioning

confidence: 99%

Distributed Computing Optimization in Unmanned Aerial Vehicle Swarm Cooperative Networks

Luo,

Zhang,

Shi

et al. 2024

CIT. J. comput. inf. technol

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The Unmanned Aerial Vehicle (UAV) swarm cooperative networks across diverse domains present significant challenges in management and control to maximize collaborative efficiency, particularly in applications for large-scale and dynamic environments where real-time coordination is essential. This challenge has led to the development of a UAV swarm cooperative network flow prediction model, facilitating the strategic anticipation of network dynamics. A novel algorithm for distributed, finite-time cooperative control is introduced, grounded in this model. This algorithm optimizes the operational efficiency and control precision of UAV systems, while simultaneously augmenting the collaborative efficiency and stability of the UAV swarms. It marks a significant advancement in distributed computing strategies, offering a viable solution for the real-time coordination challenges in extensive UAV swarm cooperative networks. The proposed approach leverages multi-agent technology, integrating spatial-temporal constraints, location limitations, and path selection in cooperative behavior for dynamic and effective network management. This study not only enhances the understanding of UAV swarm dynamics but also contributes to the practical application of UAV swarms in areas requiring precise coordination and robust network stability.

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Section: Introductionmentioning

confidence: 99%