典型文献
Positioning error compensation of an industrial robot using neural networks and experimental study
文献摘要：
Due to the characteristics of high efficiency,wide working range,and high flexibility,industrial robots are being increasingly used in the industries of automotive,machining,electrical and electronic,rubber and plastics,aerospace,food,etc.Whereas the low positioning accuracy,resulted from the serial configuration of industrial robots,has limited their further developments and applications in the field of high requirements for machining accuracy,e.g.,aircraft assembly.In this paper,a neural-network-based approach is proposed to improve the robots' positioning accuracy.Firstly,the neural network,optimized by a genetic particle swarm algorithm,is con-structed to model and predict the positioning errors of an industrial robot.Next,the predicted errors are utilized to realize the compensation of the target points at the robot's workspace.Finally,a series of experiments of the KUKA KR 500-3 industrial robot with no-load and drilling scenarios are implemented to validate the proposed method.The experimental results show that the position-ing errors of the robot are reduced from 1.529 mm to 0.344 mm and from 1.879 mm to 0.227 mm for the no-load and drilling conditions,respectively,which means that the position accuracy of the robot is increased by 77.6％ and 87.9％ for the two experimental conditions,respectively.
文献关键词：
中图分类号：
作者姓名：
Bo LI;Wei TIAN;Chufan ZHANG;Fangfang HUA;Guangyu CUI;Yufei LI
作者机构：
College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Hebei Hanguang Industry Co.,Ltd,Handan 056017,China
文献出处：
引用格式：
[1]Bo LI;Wei TIAN;Chufan ZHANG;Fangfang HUA;Guangyu CUI;Yufei LI-.Positioning error compensation of an industrial robot using neural networks and experimental study)[J].中国航空学报（英文版）,2022(02):346-360
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B类：
Positioning,compensation,industrial,using,neural,networks,experimental,study,Due,characteristics,high,efficiency,wide,working,range,flexibility,robots,are,being,increasingly,used,industries,automotive,machining,electrical,electronic,rubber,plastics,aerospace,food,etc,Whereas,low,positioning,accuracy,resulted,from,serial,configuration,has,limited,their,further,developments,applications,field,requirements,aircraft,assembly,In,this,paper,approach,proposed,improve,Firstly,optimized,by,genetic,particle,swarm,algorithm,structed,model,errors,Next,predicted,utilized,realize,target,points,workspace,Finally,series,experiments,KUKA,KR,no,load,drilling,scenarios,implemented,validate,method,results,show,that,reduced,conditions,respectively,which,means,increased
AB值：
0.542453
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