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Application of Multiobjective Genetic Programming to the Design of Robot Failure Recognition Systems

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2 Author(s)
Yang Zhang ; Dept. of Electron. & Electr. Eng., Univ. of Sheffield, Sheffield ; Rockettt, P.I.

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.

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Automation Science and Engineering, IEEE Transactions on  (Volume:6 ,  Issue: 2 )