About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
cc 16(8): e5

Research Article

Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm

Download1208 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eai.3-12-2015.2262390,
        author={Matthew Johnson and Daniel Brown},
        title={Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm},
        journal={EAI Endorsed Transactions on Collaborative Computing},
        volume={2},
        number={8},
        publisher={ACM},
        journal_a={CC},
        year={2016},
        month={5},
        keywords={swarm robotics, evolutionary algorithms, computation-free robot, controlling collective behaviors},
        doi={10.4108/eai.3-12-2015.2262390}
    }
    
  • Matthew Johnson
    Daniel Brown
    Year: 2016
    Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm
    CC
    EAI
    DOI: 10.4108/eai.3-12-2015.2262390
Matthew Johnson1,*, Daniel Brown1
  • 1: Air Force Research Laboratory
*Contact email: matthew.johnson.151@us.af.mil

Abstract

Designing and controlling the collective behavior of a swarm often requires complex range, bearing sensors, and peer-to-peer communication strategies. Recent work studying swarm of robots that have no computational power has shown that complex behaviors such as aggregation and object clustering can be produced from extremely simple control policies and sensing capability. We extend previous work on computation-free swarm behaviors and show that it is possible to evolve simple control policies to form a perimeter around a target, rendezvous to a specific location, and perform foraging. We also demonstrate that simple manipulations of the environment can be used to control, these collective behaviors. The robustness and expressiveness of these behaviors, combined with the simple requirements for control and sensing, demonstrate the feasibility of implementing swarm behaviors at small scales or in extreme environments.

Keywords
swarm robotics, evolutionary algorithms, computation-free robot, controlling collective behaviors
Published
2016-05-24
Publisher
ACM
http://dx.doi.org/10.4108/eai.3-12-2015.2262390

Copyright © 2015 M. Johnson and D. Brown, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL