Practical Aspects of the Dynamic Model Identification of Industrial Robots
DOI:
https://doi.org/10.37537/rev.elektron.5.2.138.2021Keywords:
robot, parametric identification, robot dynamics, trajectory optimizationAbstract
The practical aspects of the dynamical parameter identification method of an ABB IRB140 robot (off-line calibration procedure) are presented, such as identifiability, reduction to base parameters, inclusion of the measurements noise model and their influence on estimation uncertainty, scaling, and prior knowledge incorporation. A remarkable result is the calculation of the trajectories that provide a set of persistently excitatory signals of the dynamics in order to improve the estimation. The signals preprocessing is another relevant aspect since, to reduce the effect of noise, the excitation is limited in bandwidth and the derivatives of the joint positions are calculated in the transformed space.Downloads
References
M. W. Spong and M. Vidyasagar, Robot Dynamics and Control. NY: Wiley & Sons, 1989.
D. Zeida, “Desarrollo de un paquete de simulación para robots en un ambiente con manejo de ecuaciones simbólicas (mathemática).” Tesina de Graduación en Ingeniería Electrónica, FIUBA, 1996.
A. Oubiña, “Identificación de parámetros dinámicos de robots para calibración y control adaptativo.” Tesis de Graduación en Ingeniería Electrónica, FIUBA, 1996.
M. Anigstein, “Dinámica de manipuladores robóticos.” Tesis Doctoral, FIUBA, 2002.
A. Luca and W. Book, Robots with Flexible Elements, pp. 287–319. 01 2008.
J. M. Hollerbach, W. Khalil, and M. Gautier, “Model identification,” in Springer Handbook of Robotics, pp. 113–138, 2016.
C. Atkeson, C. An, and J. Hollerbach, “Estimation of inertial parameters of manipulator loads and links,” Int J Robot Res, vol. 5, no. 3, pp. 101–119, 1986.
M. Gautier, “Identification of robots dynamics,” IFAC Proceedings Volumes, vol. 19, no. 14, pp. 125–130, 1986.
B. Armstrong, “On finding exciting trajectories for identification experiments involving systems with nonlinear dynamics,” The International Journal of Robotics Research, vol. 8, no. 6, pp. 28–48, 1989.
M. Gautier and W. Khalil, “Exciting trajectories for the identification of base inertial parameters of robots,” The International Journal of Robotics Research, vol. 11, no. 4, pp. 362–375, 1992.
M. Brunot, A. Janot, P. Young, and F. Carrillo, “An improved instrumental variable method for industrial robot model identification,” Control Engineering Practice, vol. 74, 03 2018.
W. Khalil and E. Dombre, Modeling, Identification and Control of Robots. USA: Taylor & Francis, Inc., 2002.
J. Swevers, C. Ganseman, D. B. Tukel, J. de Schutter, and H. Van Brussel, “Optimal robot excitation and identification,” IEEE Transactions on Robotics and Automation, vol. 13, pp. 730–740, Oct 1997.
J. Swevers, W. Verdonck, and J. Schutter, “Dynamic model identification for industrial robots,” Control Systems, IEEE, vol. 27, pp. 58 – 71, 11 2007.
K. Yoshida, N. Ikeda, and H. Mayeda, “Experimental study of the identification methods for an industrial robot manipulator,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 1, pp. 263–270, July 1992.
J. Wu, J. Wang, and Z. You, “An overview of dynamic parameter identification of robots,” Robotics and Computer-Integrated Manufacturing, vol. 26, no. 5, pp. 414–419, 2010.
P. O. Vandanjon, M. Gautier, and P. Desbats, “Identification of robots inertial parameters by means of spectrum analysis,” in Proceedings of 1995 IEEE International Conference on Robotics and Automation, vol. 3, pp. 3033–3038 vol.3, May 1995.
ISO, “Manipulating industrial robots – performance criteria and related test methods,” standard, International Organization for Standardization, Geneva, CH, Apr. 1998.
ABB, System Data Types and Routines. ABB Robotics AB, S-721 68 Vasteras, Sweden, 4.0 ed., 2000.
Downloads
Published
Issue
Section
License
The authors who publish in this journal agree with terms established in the license Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)