Optimziation methods for beacon based foraging algorithms

Christopher Sanford, Jae Oh

Research output: Chapter in Book/Entry/PoemConference contribution

Abstract

Beacon-based Robotic foraging is inspired by nature’s ability to create efficient explorers and gatherers, and imposes a number of constraints on how agents can interact. In decentralized models, the robots must maintain chains of communication, effectively explore areas, and start collecting from discovered targets. Previous approaches have used a beacon-based technique, which is dependent on swarm size to environment size ratios, and do not have guarantees on finding all targets. This paper outlines the issues in these approaches and offers solutions to finding targets reliably, robust task allocations, and efficient beacon network. We verify our techniques by providing metrics of successful swarm size to environment size ratios, robot congestion improvement, and target utility independent measurements for gathering.

Original languageEnglish (US)
Title of host publicationRecent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Proceedings
EditorsOtmane Ait Mohamed, Malek Mouhoub, Samira Sadaoui, Moonis Ali
PublisherSpringer Verlag
Pages22-33
Number of pages12
ISBN (Print)9783319920573
DOIs
StatePublished - 2018
Event31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2018 - Montreal, Canada
Duration: Jun 25 2018Jun 28 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10868 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2018
Country/TerritoryCanada
CityMontreal
Period6/25/186/28/18

Keywords

  • Foraging
  • Multi-agents

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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