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Digital Twin for Human-Robot Interactive Welding and welder behavior analysis

IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 334-343页

作者： Qiyue Wang Wenhua Jiao Peng Wang YuMing Zhang Institute for Sustainable Manufacturing and the Department of Electrical and Computer Engineering University of KentuckyLexingtonKY 40506 USA the Institute for Sustainable Manufacturing and the Department of Electrical and Computer Engineering and also with the Department of Mechanical EngineeringUniversity of KentuckyLexingtonKY 40506 USA

This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior *** humanrobot interaction(HRI)working style helps to enhance human users'operational productivity and comfort;while data-driven welder behavior analysis benefits to further novice welder *** HRI system includes three modules:1)a human user who demonstrates the welding operations offsite with her/his operations recorded by the motion-tracked handles;2)a robot that executes the demonstrated welding operations to complete the physical welding tasks onsite;3)a DT system that is developed based on virtual reality(VR)as a digital replica of the physical human-robot interactive welding *** DT system bridges a human user and robot through a bi-directional information flow:a)transmitting demonstrated welding operations in VR to the robot in the physical environment;b)displaying the physical welding scenes to human users in *** to existing DT systems reported in the literatures,the developed one provides better capability in engaging human users in interacting with welding scenes,through an augmented *** verify the effectiveness,six welders,skilled with certain manual welding training and unskilled without any training,tested the system by completing the same welding job;three skilled welders produce satisfied welded workpieces,while the other three unskilled do not.A data-driven approach as a combination of fast Fourier transform(FFT),principal component analysis(PCA),and support vector machine(SVM)is developed to analyze their *** an operation sequence,i.e.,motion speed sequence of the welding torch,frequency features are firstly extracted by FFT and then reduced in dimension through PCA,which are finally routed into SVM for *** trained model demonstrates a 94.44%classification accuracy in the testing *** successful pattern recognition in skilled

关键词： Digital twin(DT) human-robot interaction(HRI) machine learning virtual reality(VR) welder behavior analysis

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