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Identification of Robot Dynamics: An Application of Recursive Estimation

In: Adaptive and Learning Systems

Author

Listed:
  • Charles P. Neuman

    (Carnegie-Mellon University, Department of Electrical and Computer Engineering, The Robotics Institute)

  • Pradeep K. Khosla

    (Carnegie-Mellon University, Department of Electrical and Computer Engineering, The Robotics Institute)

Abstract

To synthesize robust robot parameter identification algorithms, we outline the fundamental properties of the Newton-Euler (N-E) and Lagrange-Euler (L-E) formulations of robot dynamics. We transform the nonlinear (in dynamic parameters) N-E dynamic robot model into the equivalent linear (in dynamic parameters) L-E dynamic robot model. We cast the L-E torque/force error model into the series and parallel identifier structures for on-line and off-line robot parameter estimation. To illustrate our approach, we identify (in simulation) the dynamic parameters of the cylindrical prototype robot and the three degreeof-freedom positioning system of the Stanford manipulator. Our identification algorithm is directly amenable to the real-time identification of the pay-load inertial characteristics and the dynamic frictional coefficients for precise trajectory control.

Suggested Citation

  • Charles P. Neuman & Pradeep K. Khosla, 1986. "Identification of Robot Dynamics: An Application of Recursive Estimation," Springer Books, in: Kumpati S. Narendra (ed.), Adaptive and Learning Systems, pages 175-194, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-1895-9_12
    DOI: 10.1007/978-1-4757-1895-9_12
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