Multivariate linear regression model based on cross-entropy for estimating disorganisation in drone formations

• Published in: Scientific reports Vol. 13; no. 1; pp. 12750 - 16
• Main Authors: Gackowska, Marta, Cofta, Piotr, Śrutek, Mścisław, Marciniak, Beata
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 07.08.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/1042; 639/705/117; 639/705/258; Collision avoidance; Disaster management; Emergency preparedness; Energy consumption; Entropy; Humanities and Social Sciences; multidisciplinary; Regression analysis; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-39926-5

Static formations of swarms of rotorcraft drones, used for example in disaster management, are subject to intrusions, and must bear the cost of holding the formation while avoiding collisions which leads to their increased energy consumption. While the behaviour of the intruder is unpredictable, the formation can have its parameters set to try to balance the cost of avoidance with its functionality. The novel model presented in this paper assists in the selection of parameter values. It is based on multivariate linear regression, and provides an estimate of the average disturbance caused by an intruder as a function of the values of the parameters of a formation. Cross-entropy is used as a metric for the disturbance, and the data based are generated through simulations. The model explains up to 54.4% of the variability in the value of the cross-entropy, providing results that are twice as good as the baseline estimator of the mean cross-entropy.