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Evolving Collision Avoidance on Autonomous Robots




Published: 2008 September
Herausgeber: Mike Hinchey and Anastasia Pagnoni and Franz Rammig and Hartmut Schmeck
Buchtitel: Biologically Inspired Collaborative Computing
Ausgabe: 268/2008
Reihe: IFIP International Federation for Information Processing
Seiten: 85-94
Verlag: Springer
Erscheinungsort: Boston
Referierte Veröffentlichung
BibTeX


Kurzfassung
Utilizing the collective behavior of a population of interacting individuals, based on rather simple local algorithms, is a promising approach for achieving complex goals. We use an onboard online evolutionary model, based on finite Moore automata, to develop collective behavior in an artificial swarm of micro-robots. Experiments have been made in simulation to achieve Collision Avoidance. The model is shown to be capable to generate the desired behavior and we present experiments for adjusting the parameters of the evolutionary optimization.

ISBN: 978-0-387-09654-4
ISSN: 1571-5736
Weitere Informationen unter: LinkLink
DOI Link: 10.1007/978-0-387-09655-1_8

Verknüpfte Tools

Organic Computing Learning Robots Arena


Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet
Evolutionäre Algorithmen, Agenten Systeme, Organic Computing, Evolutionäre Robotik