Evolving self-organizing behaviors for a swarmbot (Articolo in rivista)

Type
Label
  • Evolving self-organizing behaviors for a swarmbot (Articolo in rivista) (literal)
Anno
  • 2004-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1023/B:AURO.0000033973.24945.f3 (literal)
Alternative label
  • Dorigo M., Trianni V., Sahin E., Gross R., Labella T. H., Baldassarre G., Nolfi S., Deneubourg J.-L., Mondada F., Floreano D., Gambardella L. M. (2004)
    Evolving self-organizing behaviors for a swarmbot
    in Autonomous robots
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Dorigo M., Trianni V., Sahin E., Gross R., Labella T. H., Baldassarre G., Nolfi S., Deneubourg J.-L., Mondada F., Floreano D., Gambardella L. M. (literal)
Pagina inizio
  • 223 (literal)
Pagina fine
  • 245 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.springerlink.com/content/p2610765662v5xw1/ (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 17 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 22 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 2-3 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1. Free Univ Brussels, IRIDIA, Brussels, Belgium 2. Middle E Tech Univ, Dept Comp Engn, KOVAN, TR-06531 Ankara, Turkey 3. CNR, Inst Cognit Sci & Technol, Rome, Italy 4. Free Univ Brussels, CENOLI, B-1050 Brussels, Belgium 5. Ecole Polytech Fed Lausanne, Autonomous Syst Lab, CH-1015 Lausanne, Switzerland 6. IDSIA, USI SUPSI, Manno Lugano, Switzerland (literal)
Titolo
  • Evolving self-organizing behaviors for a swarmbot (literal)
Abstract
  • In this paper, we introduce a self-assembling and self-organizing artifact, called a swarm-bot, composed of a swarm of s-bots, mobile robots with the ability to connect to and to disconnect from each other. We discuss the challenges involved in controlling a swarm-bot and address the problem of synthesizing controllers for the swarm-bot using artificial evolution. Specifically, we study aggregation and coordinated motion of the swarm-bot using a physics-based simulation of the system. Experiments, using a simplified simulation model of the s-bots, show that evolution can discover simple but effective controllers for both the aggregation and the coordinated motion of the swarm-bot. Analysis of the evolved controllers shows that they have properties of scalability, that is, they continue to be effective for larger group sizes, and of generality, that is, they produce similar behaviors for configurations different from those they were originally evolved for. The portability of the evolved controllers to real s-bots is tested using a detailed simulation model which has been validated against the real s-bots in a companion paper in this same special issue. (literal)
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