• DocumentCode
    3458382
  • Title

    Application of ANN in Identification of Inertial Parameters of End-Effector of Robot

  • Author

    Chen, Enwei ; Liu, Zhengshi ; Gan, Fangjian

  • Author_Institution
    Hefei Univ. of Technol., Hefei
  • fYear
    2006
  • fDate
    20-23 Aug. 2006
  • Firstpage
    972
  • Lastpage
    977
  • Abstract
    Identification of inertial parameters of manipulator of a robot is an important basic problem in robot dynamical research. Algorithm and mathematical model of inertial parameters identification of robot are analyzed in this paper. General rules and advantages of application of artificial neural network in identification of parameters of system are investigated also. A novel method different from the traditional ANN problems is developed. The structure and the weights of the network constructed have special physical meanings in this method. Difficulty in obtaining the training samples, which exists in the traditional ANN for inertial parameters estimation, is resolved. This method is simple, direct and less in operand, which can be applied on the end-effector of a robot on line to estimate its inertial parameters based on the signal of sensors. Feasibility and effectiveness of this method are proved by the results of experiment carried out in a PUMA 562 robot.
  • Keywords
    end effectors; manipulator dynamics; neural nets; parameter estimation; PUMA 562 robot; artificial neural network; end-effector; inertial parameter estimation; inertial parameter identification; robot dynamical research; robot manipulator; Algorithm design and analysis; Artificial neural networks; Design optimization; Force control; Gallium nitride; Manipulator dynamics; Mathematical model; Parameter estimation; Robot sensing systems; Signal resolution; artificial neural network; inertial parameters; parameter identification; robot;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Acquisition, 2006 IEEE International Conference on
  • Conference_Location
    Shandong
  • Print_ISBN
    1-4244-0528-9
  • Electronic_ISBN
    1-4244-0529-7
  • Type

    conf

  • DOI
    10.1109/ICIA.2006.305869
  • Filename
    4097802