CaltechAUTHORS
Published 2009 | Published
Book Section - Chapter Open

Genetic programming of an artificial neural network for robust control of a 2-D path following robot

Roy, Anthony M.
Antonsson, Erik K.
Shapiro, Andrew A.
An error occurred while generating the citation.

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

Files

Roy2009p8118Detc_2008_Proceedings_Of_The_Asme_International_Design_Engineering_Technical_Conferences.pdf

Additional details

Identifiers Funding Dates
Created:
August 20, 2023
Modified:
October 20, 2023