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Abstract: In this paper we suggest a novel method to approximate the fitness function of a genetic programming approach in order to develop fast and stable gait patterns for a quadruped robot. Therefore, gait patterns are classified by so called Signal Space Detectors. We show how a Signal Space Detector can extract information about the reliability of a classification. Finally, we demonstrate how this information can be used to replace conventional time-consuming fitness modules like real-world... (Update)
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BibTeX entry: (Update)
I. Dahm and J. Ziegler. Using artificial neural networks to construct a meta-model for the evolution of gait patterns. In Proceedings of the 5th International Conference on Climbing and Walking Robots (CLAWAR 2002. http://citeseer.ist.psu.edu/dahm02using.html More
@misc{ dahm02using,
author = "I. Dahm and J. Ziegler",
title = "Using artificial neural networks to construct a meta-model for the evolution
of gait patterns",
text = "I. Dahm and J. Ziegler. Using artificial neural networks to construct a
meta-model for the evolution of gait patterns. In Proceedings of the 5th
International Conference on Climbing and Walking Robots (CLAWAR 2002.",
year = "2002",
url = "citeseer.ist.psu.edu/dahm02using.html" }
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5 Low Complexity Signal Space Detector for (1,7)-Coded Partial.. (context) - Kim, Moon - 1998
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3 Automatic generation of control programs for walking robots .. - Busch, Ziegler et al. - 2002
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1 Soft-output signal space detectors (s3d (context) - Schmermbeck, Stromberg - 2002
1 InvKinWalkingEngine - kurze Beschreibung der Parameter (context) - Risler - 2002
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