Automatic Generation of Kinematic Models for the Conversion of Human Motion Capture Data into Humanoid Robot Motion

نویسندگان

  • Aleš Ude
  • Curtis Man
  • Marcia Riley
  • Christopher G. Atkeson
چکیده

Human motion capture is a promising technique for the generation of humanoid robot motions. To convert human motion into humanoid robot motion, we need to relate the humanoid robot kinematics to the kinematics of a human performer. In this paper we propose an automatic approach for scaling of humanoid robot kinematic parameters to the kinematic parameters of a human performer. The kinematic model is constructed directly from the motion capture data without any manual measurements. We discuss the use of the resulting kinematic model for the generation of humanoid robot motions based on the observed human motions. The results of the proposed technique on real human motion capture data are presented.

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تاریخ انتشار 2000