Phi Clust: Pheromone-Based Aggregation for Robotic Swarms

Farshad Arvin, Ali Emre Turgut, Tomas Krajnik, Salar Rahimi, Ilkin Ege Okay, Shigang Yue, Simon Watson, Barry Lennox

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we proposed a pheromone-based aggregation method based on the state-of-the-art BEECLUST algorithm. We investigated the impact of pheromone-based communication on the efficiency of robotic swarms to locate and aggregate at areas with a given cue. In particular, we evaluated the impact of the pheromone evaporation and diffusion on the time required for the swarm to aggregate. In a series of simulated and real-world evaluation trials, we demonstrated that augmenting the BEECLUST method with artificial pheromone resulted in faster aggregation times.

Original languageEnglish
Title of host publication2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PublisherIEEE
Pages4288-4294
Number of pages7
ISBN (Electronic)9781538680940
DOIs
Publication statusPublished - 27 Dec 2018
Event2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018 - Madrid, Spain
Duration: 1 Oct 20185 Oct 2018

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
Country/TerritorySpain
CityMadrid
Period1/10/185/10/18

Keywords

  • Aggregation
  • Bio-inspired
  • Pheromone
  • Swarm Robotics

Research Beacons, Institutes and Platforms

  • Dalton Nuclear Institute

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