• DocumentCode
    1235046
  • Title

    Virtual assembly with biologically inspired intelligence

  • Author

    Yuan, Xiaobu ; Yang, Simon X.

  • Author_Institution
    Sch. of Comput. Sci., Windsor Univ., Ont., Canada
  • Volume
    33
  • Issue
    2
  • fYear
    2003
  • fDate
    5/1/2003 12:00:00 AM
  • Firstpage
    159
  • Lastpage
    167
  • Abstract
    This paper investigates the introduction of biologically inspired intelligence into virtual assembly. It develops a approach to assist product engineers making assembly-related manufacturing decisions without actually realizing the physical products. This approach extracts the knowledge of mechanical assembly by allowing human operators to perform assembly operations directly in the virtual environment. The incorporation of a biologically inspired neural network into an interactive assembly planner further leads to the improvement of flexible product manufacturing, i.e., automatically producing alternative assembly sequences with robot-level instructions for evaluation and optimization. Complexity analysis and simulation study demonstrate the effectiveness and efficiency of this approach.
  • Keywords
    assembly planning; digital simulation; industrial robots; interactive systems; knowledge acquisition; knowledge based systems; neural nets; optimisation; production engineering computing; alternative assembly sequences; assembly-related manufacturing decisions; biologically inspired intelligence; biologically inspired neural network; complexity analysis; flexible product manufacturing; interactive assembly planner; knowledge extraction; mechanical assembly; optimization; product engineers; robot-level instructions; virtual assembly; Biological system modeling; Humans; Intelligent robots; Manipulators; Manufacturing automation; Neural networks; Robot programming; Robotic assembly; Robotics and automation; Virtual reality;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1094-6977
  • Type

    jour

  • DOI
    10.1109/TSMCC.2003.813149
  • Filename
    1211123