@inbook{eb30e7d016fb48a69ad36430baf2db70,
title = "The Cooperative Hunters - Efficient and Scalable Drones Swarm for Multiple Targets Detection",
abstract = "This work examines the Cooperative Hunters problem, where a swarm of Unmanned Air Vehicles (UAVs) is used for searching after one or more “evading targets”, which freely maneuver in a predefined area while trying to avoid detection by the swarm{\textquoteright}s drones. By arranging themselves into an efficient geometric collaborative flight formation, the drones optimize their integrated sensing capabilities, enabling the completion of a successful search of a rectangular territory. This designed is shown to be able to guarantee the detection of the targets, even in cases where the targets are faster than the swarm{\textquoteright}s drones and have better sensors. This is achieved through the inherent scalability of the proposed design which can compensate any addition to the targets{\textquoteright} ability to maneuver or foresee the behavior of the drones with an increase in the number of drones.",
author = "Yaniv Altshuler and Alex Pentland and Bruckstein, {Alfred M.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.",
year = "2018",
doi = "https://doi.org/10.1007/978-3-319-63604-7_7",
language = "الإنجليزيّة",
isbn = "978-3-319-63602-3",
volume = "729",
series = "Studies in Computational Intelligence",
pages = "187--205",
booktitle = "SWARMS AND NETWORK INTELLIGENCE IN SEARCH",
}