DocumentCode :
2661950
Title :
Development of evolutionary and self-assembling robot-organisms
Author :
Levi, Paul
Author_Institution :
Inst. of Parallel & Distrib. Syst., Univ. of Stuttgart, Stuttgart, Germany
fYear :
2009
fDate :
9-11 Nov. 2009
Firstpage :
1
Lastpage :
6
Abstract :
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 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 ¿operating systems¿ to control and to operate symbiotic robot organisms.
Keywords :
learning (artificial intelligence); robots; self-assembly; sensor fusion; artificial genome; artificial multicellular robot-organisms; cognitive maps; cognitive sensor data fusion; embryogenetic formed body; evolutionary robot-organisms; fitness-based learning; genetic-based learning; self-assembling robot-organisms; symbiotic robotics; Bioinformatics; Cognitive robotics; Control systems; Embryo; Genetics; Genomics; Organisms; Robots; Sensor fusion; Symbiosis; Collective robotics; adaptability; artificial evolution; self-organization; swarm intelligence; symbiotic multicellular robots; synergetics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Micro-NanoMechatronics and Human Science, 2009. MHS 2009. International Symposium on
Conference_Location :
Nagoya
Print_ISBN :
978-1-4244-5094-7
Electronic_ISBN :
978-1-4244-5095-4
Type :
conf
DOI :
10.1109/MHS.2009.5352063
Filename :
5352063
Link To Document :
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