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A Neural Network Based Method for Shape Measurement in Steel Plate Forming Robot

  • Hua Xu
  • Peifa Jia
  • Xuegong Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3498)

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.

Keywords

Steel Plate Robot System Space Relation Fuzzy Reasoning Shape Measurement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hua Xu
    • 1
  • Peifa Jia
    • 1
  • Xuegong Zhang
    • 2
  1. 1.State Key Laboratory of Intelligent Technology and SystemsTsinghua UniversityBeijingChina
  2. 2.Department of AutomationTsinghua UniversityBeijingChina

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