• DocumentCode
    3070873
  • Title

    Connectionist-genetic based algorithm for positioning industrial manipulator

  • Author

    Tomic, M. ; Miloradovic, B. ; Jankovic, Marija

  • Author_Institution
    Robot. Lab., Inst. Mihailo Pupin, Belgrade, Serbia
  • fYear
    2012
  • fDate
    20-22 Sept. 2012
  • Firstpage
    59
  • Lastpage
    64
  • Abstract
    In this paper the solution of inverse kinematics problem and positioning of the industrial manipulator (ROBED03) with five degrees of freedom are presented. The algorithm is based on combination of Artificial Neural Networks (ANN) and Genetic Algorithm (GA).ANN was used for rough positioning providing the inputs for GA which performs precise adjustment. The algorithm was successfully tested in robot´s working space.
  • Keywords
    genetic algorithms; industrial manipulators; inverse problems; manipulator kinematics; neural nets; position control; ANN; GA; ROBED03; artificial neural networks; connectionist-genetic based algorithm; genetic algorithm; industrial manipulator; inverse kinematics problem; precise adjustment; rough positioning; Artificial neural networks; Genetic algorithms; Joints; Kinematics; Manipulators; Trajectory; Genetic Algorithms; Inverse kinematics; Neural Network and Robot kinematics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on
  • Conference_Location
    Belgrade
  • Print_ISBN
    978-1-4673-1569-2
  • Type

    conf

  • DOI
    10.1109/NEUREL.2012.6419964
  • Filename
    6419964
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3070873