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Search Strategies and Specifications in a Swarm versus Swarm Context

Published online by Cambridge University Press:  02 March 2021

Ali Moltajaei Farid Open the ORCID record for Ali Moltajaei Farid [Opens in a new window] ,
Md Abdus Samad Kamal  and
Simon Egerton
Ali Moltajaei Farid*
Affiliation:
School of Information Technology, Monash University, Subang Jaya, Malaysia Monash Swarm Robotics Laboratory, Monash University, Clayton Campus, Melbourne, VIC3800, Australia
Md Abdus Samad Kamal
Affiliation:
Division of Mechanical Science and Technology, Graduate School of Science and Technology, Gunma University, Kiryu376-8515, Japan E-mail: MASKAMAL@ieee.org
Simon Egerton
Affiliation:
Department of Computer Science, Electrical Engineering, La Trobe University, Bendigo, Australia E-mail: S.EGERON@latrobe.edu.au
*
*Corresponding author. E-mail: ali.farid@monash.edu
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Summary

This paper proposes and evaluates swarming mechanisms of patrolling unmanned aerial vehicles (UAVs) that can collectively search a region for intruding UAVs. The main contributions include the development of multi-objective searching strategies and investigation of the required sensor configurations for the patrolling UAVs. Numerical results reveal that it is sometimes better to search through a region with a single swarm rather than multiple swarms deployed over sub-regions. Moreover, a large communication range does not necessarily improve search performances, and the patrolling swarm must have a speed close to the speed of the intruding UAVs to maximize the search performances.

Keywords

SwarmSearchUAVsSwarm versus swarmOptimization
Type
Article
Information
Robotica , Volume 39 , Issue 11 , November 2021 , pp. 1909 - 1925
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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