This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior analysis.This humanrobot interaction(HRI)working style helps to ...This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior analysis.This 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 training.This 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 environment.The 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 VR.Compared 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 VR.To 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 behaviors.Given 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 classification.The trained model demonstrates a 94.44%classification accuracy in the testing dataset.The successful pattern recognition in skilled welder operations should benefit to accelerate novice welder training.展开更多
Industrial robots are currently applied for ship sub-assembly welding to replace welding workers because of the intelligent production and cost savings.In order to improve the efficiency of the robot system,a digital ...Industrial robots are currently applied for ship sub-assembly welding to replace welding workers because of the intelligent production and cost savings.In order to improve the efficiency of the robot system,a digital twin system of welding path planning for the arc welding robot in ship sub-assembly welding is proposed in this manuscript to achieve autonomous planning and generation of the welding path.First,a five-dimensional digital twin model of the dual arc welding robot system is constructed.Then,the system kinematics analysis and calibration are studied for communication realization between the virtual and the actual system.Besides,a topology consisting of three bounding volume hierarchies(BVH)trees is proposed to construct digital twin virtual entities in this system.Based on this topology,algorithms for welding seam extraction and collision detection are presented.Finally,the genetic algorithm and the RRT-Connect algorithm combined with region partitioning(RRT-Connect-RP)are applied for the welding sequence global planning and local jump path planning,respectively.The digital twin system and its path planning application are tested in the actual application scenario.The results show that the system can not only simulate the actual welding operation of the arc welding robot but also realize path planning and real-time control of the robot.展开更多
文摘This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior analysis.This 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 training.This 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 environment.The 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 VR.Compared 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 VR.To 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 behaviors.Given 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 classification.The trained model demonstrates a 94.44%classification accuracy in the testing dataset.The successful pattern recognition in skilled welder operations should benefit to accelerate novice welder training.
基金This work was supported by the National Natural Science Foundation of China(Nos.62076095 and 61973120)National Key Research and Development Program(No.2022YFB4602104).
文摘Industrial robots are currently applied for ship sub-assembly welding to replace welding workers because of the intelligent production and cost savings.In order to improve the efficiency of the robot system,a digital twin system of welding path planning for the arc welding robot in ship sub-assembly welding is proposed in this manuscript to achieve autonomous planning and generation of the welding path.First,a five-dimensional digital twin model of the dual arc welding robot system is constructed.Then,the system kinematics analysis and calibration are studied for communication realization between the virtual and the actual system.Besides,a topology consisting of three bounding volume hierarchies(BVH)trees is proposed to construct digital twin virtual entities in this system.Based on this topology,algorithms for welding seam extraction and collision detection are presented.Finally,the genetic algorithm and the RRT-Connect algorithm combined with region partitioning(RRT-Connect-RP)are applied for the welding sequence global planning and local jump path planning,respectively.The digital twin system and its path planning application are tested in the actual application scenario.The results show that the system can not only simulate the actual welding operation of the arc welding robot but also realize path planning and real-time control of the robot.
