The Cooperative Hunters - Efficient and Scalable Drones Swarm for Multiple Targets Detection

Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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’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’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’ ability to maneuver or foresee the behavior of the drones with an increase in the number of drones.

Original languageEnglish
Title of host publicationSWARMS AND NETWORK INTELLIGENCE IN SEARCH
Pages187-205
Number of pages19
Volume729
DOIs
StatePublished - 2018

Publication series

NameStudies in Computational Intelligence

ASJC Scopus subject areas

  • Artificial Intelligence

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