Artikel in Tagungsband INPROC-2009-108

Bibliograph.
Daten
Levi, Paul: Development of Evolutionary and Self-Assembling Robot-Organisms.
In: IEEE (Hrsg): Proc. of 20th Anniversary MHS2009 & Micro-Nano Global COE.
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 1-6, englisch.
Nagoya, Japan: -, 8. November 2009.
ISBN: 978-1-4244-5095-4.
Artikel in Tagungsband (Konferenz-Beitrag).
Körperschaft20th Anniversary MHS2009 & Micro-Nano Global COE
CR-Klassif.I.2.9 (Robotics)
I.2.10 (Vision and Scene Understanding)
I.2.11 (Distributed Artificial Intelligence)
KeywordsCollective robotics; symbiotic multicellular robots; artificial evolution; adaptability; synergetics; self-organization; swarm intelligence
Kurzfassung

Symbiotic robotics is a discipline within collective robotics that is concerned with artificial multi-cellular robot-organisms that define their morphological structure by aggregation through self-assembling and they are also able to disaggregate afterwards. This contribution is concerned to the description of evolutionary and cognitive principles that governs such a symbiotic cycle to build artificial organisms of different forms and operate with them. The evolutionary approach starts with a artificial genome, will be continued by the insertion of different types of regulative cycles, and ends up in an embryogenetic formed body. Hereby there is differentiation between the genetic based learning and the fitness based learning. Further there are dominant differences between multi-cellular organism and structured cooperative aggregations of swarm members. The cognitive approach is focused on cognitive maps, on cognitive sensor data fusion and finally to the definition of information that governs the the process of organism formation and body survival in a given environment. This more engineering oriented approach is used to build all HW-components and all kinds of embedded âoperating systemsâ to control and to operate symbiotic robot organisms.

Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Bildverstehen
Eingabedatum14. Dezember 2009
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