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Structure and function of evolved neuro-controllers for autonomous robots

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The artificial life approach to evolutionary robotics is used as a fundamental framework for the development of a modular neural control of autonomous mobile robots. The applied evolutionary technique is especially designed to grow different neural structures with complex dynamical properties. This is due to a modular neurodynamics approach to cognitive systems, stating that cognitive processes are the result of interacting dynamical neuro-modules. The evolutionary algorithm is described, and a few examples for the versatility of the procedures are given. Besides solutions for standard tasks like exploration, obstacle avoidance and tropism, also the sequential evolution of morphology and control of a biped is demonstrated. A further example describes the co-evolution of different neuro-controllers co-operating to keep a gravitationally driven art-robot in constant rotation.
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Keywords: evolution of morphology; modular neuro‐dynamics; nonlinear robot control; perception–action systems; structure evolution

Document Type: Research Article

Affiliations: Fraunhofer Institute for Autonomous Intelligent Systems (AIS), Schloss Birlinghoven, 53754, Sankt Augustin, Germany, {martin.huelse, steffen.wischmann, frank.pasemann}@ais.fraunhofer.de

Publication date: 01 December 2004

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