• DocumentCode
    2617691
  • Title

    Using Adaptive Genetic Algorithm to the Placement of Serial Robot Manipulator

  • Author

    He, Guangzhong ; Gao, Hongming ; Zhang, Guangjun ; Wu, Lin

  • Author_Institution
    Nat. Key Lab. of Adv. Welding Production Technol., Harbin Inst. of Technol.
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents mathematical methods for the placement of serial robot manipulators with respect to pre-defined target points in arc welding applications where robot is mounted on a gantry or a multi-freedom crossbeam and manual programming of the robot system is rather difficult to complete. The robot placement problem is a nonlinear optimization problem, the traditional optimization methods can not solve it satisfactorily. In this paper the adaptive genetic algorithm (ASAGA) is adopted and introduced which can dynamically modify the parameters of genetic algorithms in terms of simulated annealing mechanism. Multiple kinematics criteria is presented and the objective function is constructed. The joint angles of the arm were generated by the inverse kinematics. The result shows that the ASAGA is successful in solving the robot placement problem
  • Keywords
    arc welding; genetic algorithms; manipulator kinematics; mathematical analysis; robotic welding; adaptive genetic algorithm; arc welding applications; inverse kinematics; manual programming; mathematical methods; multifreedom crossbeam; multiple kinematics; robot placement problem; serial robot manipulator; Constraint optimization; Genetic algorithms; Helium; Manipulators; Optimization methods; Production; Robot kinematics; Search methods; Service robots; Welding; genetic algorithm; inverse kinematics; manipulator; placement; welding seam;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering of Intelligent Systems, 2006 IEEE International Conference on
  • Conference_Location
    Islamabad
  • Print_ISBN
    1-4244-0456-8
  • Type

    conf

  • DOI
    10.1109/ICEIS.2006.1703222
  • Filename
    1703222