Published 2009
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Genetic programming of an artificial neural network for robust control of a 2-D path following robot
Abstract
Genetic Programs that have phenotypes created by the application of genotypes comprising rules are robust and highly scalable. Such encodings are useful for complex applications such as controller design. This paper outlines an evolutionary algorithm capable of creating a controller for 2 DOF, path following robot. The controllers are embodied by Artificial Neural Networks capable of full functionality despite multiple failures.
Additional Information
© 2008 ASME. Part of the research described in this paper was sponsored by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.Attached Files
Published - Roy2009p8118Detc_2008_Proceedings_Of_The_Asme_International_Design_Engineering_Technical_Conferences.pdf
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- Eprint ID
- 18737
- Resolver ID
- CaltechAUTHORS:20100618-141102014
- JPL/Caltech
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2010-07-08Created from EPrint's datestamp field
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2021-11-08Created from EPrint's last_modified field