An iterated greedy algorithm for finding the minimum dominating set in graphs

Casado, Alejandra; Bermudo, Sergio; López-Sánchez, Ana Dolores; Sánchez‐Oro, Jesús

doi:10.1016/j.matcom.2022.12.018

Cited by 11 publications

(1 citation statement)

References 16 publications

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“…UAVs are characterized by low cost, high flexibility, and high load capacity, and can accomplish complex cooperative flight tasks, which have strong application value in agricultural irrigation systems, military reconnaissance, traffic patrol, and other fields [1], [2], [3], and the research on cooperative UAV flight has gradually climbed in recent years. With the gradual increase of the difficulty of the mission, the formation of UAVs is also more challenging, and some more classical UAV formation control algorithms exist [4], [5], [6].In this paper, the position adjustment scheme of UAVs is obtained by a greedy algorithm according to the edge-angle relationship between neighboring UAVs and following the criterion of the minimum number of UAVs [7].…”

Section: Introductionmentioning

confidence: 99%

UAV Formation Adjustment Strategy Based on Greedy Criterion

Wang

Zhang

Yang

et al. 2023

J. Phys.: Conf. Ser.

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In order to ensure that the UAV cluster remains electromagnetically silent during the attempted formation flight, so that the emission of electromagnetic wave signalsj is minimised, a purely azimuthal passive positioning method can be used to adjust the position of the UAVs. As it is difficult to keep the UAVs in formation flying on the same horizontal plane for a long time and the initial position information of the UAVs is not known. Therefore, this paper uses the sine and cosine theorems of in-plane triangles to connect slightly deviating UAVs to a determined UAV position, and in combination with the characteristics of the model, constructs a greedy criterion based on the minimum number of UAVs required to transmit the signal, and in this way gives an adjustment scheme for the UAV position.

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