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Drone Placement for Optimal Coverage by Brain Storm Optimization Algorithm

  • Eva Tuba
  • Romana Capor-Hrosik
  • Adis Alihodzic
  • Milan Tuba
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 734)

Abstract

Unmanned aerial vehicles or drones are used in wide range of applications and one of them is area monitoring. Finding the optimal positions for drones so that the coverage is maximized, while reducing the fuel consumption represents computationally hard problem. For these kinds of problems, swarm intelligence algorithms have been successfully used. In this paper we propose recent brain storm optimization algorithm for finding the locations for static drones. Optimal drone placement maximizes the number of covered targets while minimizing drones altitude. The proposed method was tested in two different environments, with uniformly and clustered deployed targets. Based on the obtained results it can be concluded that brain storm optimization is appropriate for solving drone placement problem in both considered environments.

Keywords

Drone placement Area coverage Swarm intelligence Brain storm optimization 

Notes

Acknowledgment

This research is supported by the Ministry of Education, Science and Technological Development of Republic of Serbia, Grant No. III-44006.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Eva Tuba
    • 1
  • Romana Capor-Hrosik
    • 2
  • Adis Alihodzic
    • 3
  • Milan Tuba
    • 4
  1. 1.Faculty of Informatics and ComputingSingidunum UniversityBelgradeSerbia
  2. 2.Institute for Marine and Coastal ResearchUniversity of DubrovnikDubrovnikCroatia
  3. 3.Faculty of MathematicsUniversity of SarajevoSarajevoBosnia and Herzegovina
  4. 4.Department of Technical SciencesState University of Novi PazarNovi PazarSerbia

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