Skip to main content
Article thumbnail
Location of Repository

Application of multiobjective genetic programming to the design of robot failure recognition systems

By Y. Zhang and P.I. Rockett

Abstract

We present an evolutionary approach using multiobjective genetic programming (MOGP) to derive optimal feature extraction preprocessing stages for robot failure detection. This data-driven machine learning method is compared both with conventional (nonevolutionary) classifiers and a set of domain-dependent feature extraction methods. We conclude MOGP is an effective and practical design method for failure recognition systems with enhanced recognition accuracy over conventional classifiers, independent of domain knowledge

Publisher: Institute of Electrical and Electronics Engineers
Year: 2009
OAI identifier: oai:eprints.whiterose.ac.uk:8566

Suggested articles


To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.