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  Self-organized adaptation of a simple neural circuit enables complex robot behaviour

Steingrube, S., Timme, M., Wörgötter, F., & Manoonpong, P. (2010). Self-organized adaptation of a simple neural circuit enables complex robot behaviour. Nature Physics, 6, 224-230. doi:10.1038/nphys1508.

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 Creators:
Steingrube, Silke, Author
Timme, Marc1, Author           
Wörgötter, Florentin, Author
Manoonpong, Poramate1, Author           
Affiliations:
1Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063295              

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 Abstract: Controlling sensori-motor systems in higher animals or complex robots is a challenging combinatorial problem, because many sensory signals need to be simultaneously coordinated into a broad behavioural spectrum. To rapidly interact with the environment, this control needs to be fast and adaptive. Present robotic solutions operate with limited autonomy and are mostly restricted to few behavioural patterns. Here we introduce chaos control as a new strategy to generate complex behaviour of an autonomous robot. In the presented system, 18 sensors drive 18 motors by means of a simple neural control circuit, thereby generating 11 basic behavioural patterns (for example, orienting, taxis, self-protection and various gaits) and their combinations. The control signal quickly and reversibly adapts to new situations and also enables learning and synaptic long-term storage of behaviourally useful motor responses. Thus, such neural control provides a powerful yet simple way to self-organize versatile behaviours in autonomous agents with many degrees of freedom.

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Language(s): eng - English
 Dates: 2010-01-17
 Publication Status: Published in print
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 Rev. Type: Peer
 Identifiers: eDoc: 528771
DOI: 10.1038/nphys1508
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Title: Nature Physics
Source Genre: Journal
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Pages: - Volume / Issue: 6 Sequence Number: - Start / End Page: 224 - 230 Identifier: -