A hormone-based controller for evolutionary multi-modular robotics : From single modules to gait learning

Hamann, Heiko; Stradner, Jurgen; Schmickl, Thomas; Crailsheim, Karl

A hormone-based controller for evolutionary multi-modular robotics : From single modules to gait learning

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2010

Autor:innen

Hamann, Heiko

Stradner, Jurgen

Schmickl, Thomas

Crailsheim, Karl

DOI (zitierfähiger Link)

https://doi.org/10.1109/CEC.2010.5585994

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

IEEE Congress on Evolutionary Computation. Piscataway, NJ: IEEE, 2010, C-7784. ISSN 1089-778X. eISSN 1941-0026. ISBN 978-1-4244-6911-6. Available under: doi: 10.1109/CEC.2010.5585994

Zusammenfassung

For any embodied, mobile, autonomous agent it is essential to control its actuators appropriately for the faced task. This holds for natural organisms as well as for robots. If several such agents have to cooperate, the coordination of actions becomes important. We present an artificial homeostatic hormone system which is a bio-inspired control paradigm. It allows to control both, a single robot as well a set of cooperating modules in multi-modular reconfigurable robotics. Our approach is inspired by chemical signal-processing and hormone control in animals. Evolutionary computation is used to adapt controllers for two distinct morphological robot configurations (uni-and multi-modular), different environmental conditions, and tasks. This approach is compared to artificial neural networks. Our results indicate, that the proposed control paradigm is well adaptable to different robot morphologies and to different environmental situations. It is able to generate behaviors for several robotic tasks and outperforms neural networks in terms of evolvability in the tested multi-modular robotic setting tested.

Fachgebiet (DDC)

004 Informatik

Konferenz

2010 IEEE Congress on Evolutionary Computation, 18. Juli 2010 - 23. Juli 2010, Barcelona, Spain

Zitieren

ISO 690

HAMANN, Heiko, Jurgen STRADNER, Thomas SCHMICKL, Karl CRAILSHEIM, 2010. A hormone-based controller for evolutionary multi-modular robotics : From single modules to gait learning. 2010 IEEE Congress on Evolutionary Computation. Barcelona, Spain, 18. Juli 2010 - 23. Juli 2010. In: IEEE Congress on Evolutionary Computation. Piscataway, NJ: IEEE, 2010, C-7784. ISSN 1089-778X. eISSN 1941-0026. ISBN 978-1-4244-6911-6. Available under: doi: 10.1109/CEC.2010.5585994

BibTex

@inproceedings{Hamann2010hormo-59958,
  year={2010},
  doi={10.1109/CEC.2010.5585994},
  title={A hormone-based controller for evolutionary multi-modular robotics : From single modules to gait learning},
  isbn={978-1-4244-6911-6},
  issn={1089-778X},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={IEEE Congress on Evolutionary Computation},
  author={Hamann, Heiko and Stradner, Jurgen and Schmickl, Thomas and Crailsheim, Karl},
  note={Article Number: C-7784}
}

RDF

<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/59958">
    <dcterms:title>A hormone-based controller for evolutionary multi-modular robotics : From single modules to gait learning</dcterms:title>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Crailsheim, Karl</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-26T15:33:27Z</dcterms:available>
    <dc:language>eng</dc:language>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2023-01-26T15:33:27Z</dc:date>
    <dcterms:abstract xml:lang="eng">For any embodied, mobile, autonomous agent it is essential to control its actuators appropriately for the faced task. This holds for natural organisms as well as for robots. If several such agents have to cooperate, the coordination of actions becomes important. We present an artificial homeostatic hormone system which is a bio-inspired control paradigm. It allows to control both, a single robot as well a set of cooperating modules in multi-modular reconfigurable robotics. Our approach is inspired by chemical signal-processing and hormone control in animals. Evolutionary computation is used to adapt controllers for two distinct morphological robot configurations (uni-and multi-modular), different environmental conditions, and tasks. This approach is compared to artificial neural networks. Our results indicate, that the proposed control paradigm is well adaptable to different robot morphologies and to different environmental situations. It is able to generate behaviors for several robotic tasks and outperforms neural networks in terms of evolvability in the tested multi-modular robotic setting tested.</dcterms:abstract>
    <dc:contributor>Hamann, Heiko</dc:contributor>
    <dc:creator>Schmickl, Thomas</dc:creator>
    <dc:contributor>Stradner, Jurgen</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Stradner, Jurgen</dc:creator>
    <dc:contributor>Schmickl, Thomas</dc:contributor>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/59958"/>
    <dcterms:issued>2010</dcterms:issued>
    <dc:creator>Hamann, Heiko</dc:creator>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Crailsheim, Karl</dc:creator>
  </rdf:Description>
</rdf:RDF>

Universitätsbibliographie

Nein