Simultaneous exploration and harvesting in multi-robot foraging

Zilong Jiao, Jae C Oh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We study the multi-robot foraging problem in an unknown environment with risks. Robots have to explore entire unknown environment without stepping into risk areas and simultaneously collect all discovered targets. We present a novel algorithm that integrates the frontier-based exploration algorithm with auction-based task-allocation. Extensive simulation studies demonstrate that our algorithm can balance the tasks of environment exploration and target collection efficiently.

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
PublisherSpringer Verlag
Pages496-502
Number of pages7
ISBN (Print)9783319920573
DOIs
StatePublished - Jan 1 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
CountryCanada
CityMontreal
Period6/25/186/28/18

Keywords

  • Auction methods
  • Multi-robot foraging
  • Target delivery

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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