This paper considers the practical implementation of a new maximum likelihood robot identification method, developed by Olsen and Petersen. In particular, the practical issue concerning the estimation of the joint velocities and accelerations from joint angle measurements, and its consequence on the parameter estimation and accuracy, is considered. Simulation and experimental results on a KUKA IR 361 industrial robot are discussed, and compared with models obtained using a much simpler weighted least squares method.
Armstrong, B.1989. On finding exciting trajectories for identification experiments involving systems with nonlinear dynamics. Int. Journal of Robotics Research8(6):28-48.
2.
Atkeson, C., An, C., and Hollerbach, J.1986. Estimation of inertial parameters of manipulators loads and links. Int. Journal of Robotics Research5(3):101-119.
3.
Fisette, P., Raucent, B., and Samin, J.-C.1993. Minimal dynamic characterization of tree-like multibody systems. In Computer-Aided Analysis of Rigid and Flexible Machan. Syst, NATO-Advanced Study Inst., Vol. II, Troia, Portugal, pp. 111-129.
4.
Ganseman, C.1998. Dynamic Modelling and Identification of Mechanisms with Application to Industrial Robots. PhD thesis, Katholieke Universiteit Leuven.
5.
Gautier, M., and Khalil, W.1992. Exciting trajectories for the identification of base inertial parameters of robots. Int. Journal of Robotics Research11(4):362-375.
6.
Golub, G.H., and Van Loan, C.F.1989. Matrix Computations. The Johns Hopkins University Press.
7.
Ljung, L.1987. System Identification, Theory for the User. Englewood Cliffs: Prentice-Hall, Inc.
8.
Nagelkerke, Nico J. D.1992. Maximum likelihood estimation of functional relationships . Lecture Notes in Statistics No. 69, Springer-Verlag, ISBN 0-387-97721-X.
9.
Norton, J.1986. An Introduction to Identification. London: Academic Press.
10.
Olsen, M.M., and Petersen, H.G.2001. A new method for estimating parameters of a dynamic robot model. IEEE Trans. on Robotics and Automation17(1):95-100.
11.
Schoukens, J., and Pintelon, R.1991. Identification of Linear Systems: A Practical Guideline to Accurate Modeling. Oxford: Pergamon Press.
12.
Swevers, J. et al. 1997. Optimal robot excitation and identification . IEEE Trans. on Robotics and Automation13(5):730-740.
13.
Torfs, D., De Schutter, J., and Swevers, J.1992. Extended bandwidth zero phase error tracking control of nonminimal phase systems. Transactions of the ASME, Journal of Dynamic Systems, Measurement, and Control114(3):347- 351, and Erratum, Vol. 114, p. 555.
