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

IEEE Transactions on Automation Science and Engineering

Volumn 6, Issue 2, 2009, Pages 372-376

  Zhang, Yang ^a   Rockett, Peter I ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Autonomous robots; Failure recognition; Feature extraction; Multiobjective genetic programming (MOGP)

Indexed keywords

AUTONOMOUS OPERATIONS; AUTONOMOUS ROBOTS; BENCHMARK DATASETS; CONTROL STRATEGIES; CONVENTIONAL CLASSIFIERS; DATA-DRIVEN; DETECTION PERFORMANCE; DOMAIN KNOWLEDGE; EVOLUTIONARY APPROACHES; FAILURE DETECTIONS; FAILURE RECOGNITION; FEATURE EXTRACTION METHODS; MACHINE LEARNING METHODS; MULTIOBJECTIVE GENETIC PROGRAMMING (MOGP); PRACTICAL DESIGN METHODS; RECOGNITION ACCURACIES; RECOGNITION SYSTEMS; ROBOTIC SYSTEMS;

BENCHMARKING; CLASSIFIERS; COMPUTER SYSTEMS PROGRAMMING; GENETIC ALGORITHMS; GENETIC PROGRAMMING; LEARNING SYSTEMS; MACHINE DESIGN; MULTIOBJECTIVE OPTIMIZATION; ROBOT PROGRAMMING; ROBOTICS; ROBOTS;

FEATURE EXTRACTION;

EID: 64049084437     PISSN: 15455955     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASE.2008.2004414     Document Type: Article

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