A neural network based method for shape measurement in steel plate forming robot

Authors:
Hua Xu;Peifa Jia;Xuegong Zhang
Affiliations:
State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, China;State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, China;Department of Automation, Tsinghua University, Beijing, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

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Abstract

Shape measurement is one of the critical problems in manufacturing robot systems. The point coordinates that we get change distinctly, because different objects to be processed own various shape forms. So it is difficult for traditional methods to get original accurate shape information. It always affects the processing results of manufacturing robot systems. According to the shipbuilding requirements, this paper proposes a dynamic and intelligent shape measurement method, which is based on the fuzzy reasoning (FR) and neural network (NN) method. FR is used to judge the relation of measured points. As the input of the NN, the fitted coordinate and the possibility of the rim point can be got. It has been demonstrated effective in Dalian Shipbuilding manufacturing robot system.