Abstract
An evolutionary autonomous failure recognition
approach is presented using multi-objective genetic
programming in this paper. It is compared with the
conventional robot failure classification algorithm.
Detailed analysis of the evolved feature extractors is
tempted on investigated problems. We conclude MOGP is
an effective and practical way to automate the process
of failure recognition system design with better
recognition accuracy and more flexibility via
optimising feature extraction stage.
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