• DocumentCode
    183882
  • Title

    A genetic algorithm approach to the kinematic synthesis of a 6-DoF parallel manipulator

  • Author

    Ferrari, Davide ; Giberti, Hermes

  • Author_Institution
    Dept. of Mech. Eng., Politec. di Milano, Milan, Italy
  • fYear
    2014
  • fDate
    8-10 Oct. 2014
  • Firstpage
    222
  • Lastpage
    227
  • Abstract
    The main applications where parallel robots are used remain until today very limited. The best known examples include flight simulators, large vibrating tables for seismic tests, pointing systems of antennas and telescopes mirrors. Common to all these robotic devices are: (1) high accuracy, (2) high velocities and accelerations, and (3) high loading capabilities: the robot itself becomes the supporting structure. This paper presents the kinetostatic synthesis for the realization of a six degrees of freedom robotic platform with Hexaglide parallel architecture. The kinetostatic synthesis was achieved through a multi-objective optimization of the geometrical parameters with a genetic algorithm. The objectives to be achieved are concerned with: (1) the coverage of the desired workspace, (2) the static forces multiplication, (3) the longitudinal size, (4) the link-to-link interference, and (5) the link-to-rail interference.
  • Keywords
    genetic algorithms; geometry; manipulator kinematics; 6-DoF parallel manipulator; Hexaglide parallel architecture; genetic algorithm approach; geometrical parameters; kinematic synthesis; kinetostatic synthesis; link-to-link interference; link-to-rail interference; longitudinal size; multiobjective optimization; parallel robots; robotic devices; six-degree-of-freedom robotic platform realization; static force multiplication; workspace coverage; Interference; Jacobian matrices; Joints; Kinematics; Optimization; Rails; Robots; HexaFloat; Hexaglide; PKMs; genetic algorithm; kinematic-kinetostatic synthesis; multi-objective optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications (CCA), 2014 IEEE Conference on
  • Conference_Location
    Juan Les Antibes
  • Type

    conf

  • DOI
    10.1109/CCA.2014.6981355
  • Filename
    6981355