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ESANN
2003

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Evolved Neurodynamics for Robot Control

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Evolved Neurodynamics for Robot Control

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Small recurrent neural network with two and three neurons are able to control autonomous robots showing obstacle avoidance and photo-tropic behaviors. They have been generated by evolutionary processes, and they demonstrate, how dynamical properties can be used for an eﬀective behavior control. Presented examples also show how sensor fusion can be obtained by evolution. Additional techniques are used to excavate the relevant neural processing mechanisms underlying speciﬁc behavior features.

Frank Pasemann, Martin Hülse, Keyan Zahedi

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ESANN 2003 | ESANN 2007 | Eﬀective Behavior Control | Recurrent Neural Network | Robots Showing Obstacle |

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2003
Where	ESANN
Authors	Frank Pasemann, Martin Hülse, Keyan Zahedi

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