Abstract
The identification of the dynamics of a standard industrial robot is solved by the application of the multivariable least square method. In order to eliminate the dominant influence of friction in gears and joints a nonlinear friction model is adapted to measured friction characteristics. Its influence is compensated in the identification step. The base parameter vector is grouped and optimal trajectories are used to identify each group. The quality of the identified model is verified by comparison of measured trajectories and torques predicted by the model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Daemi, M.; Heimann, B.: Inverse Dynamik and Identifikation von Robotermodellen, Technische Mechanik, Band 15, Heft 2, 1995, S. 107–117.
Gautier, M.; Khalil, W.: A Direct Determination of Minimum Inertial Parameters of Robots, Proc. IEEE Int. Conf. on Rob. and Autom., pp. 1682–1687, 1988.
Khalil, W.; Kleinfinger, J.F.: A new geometric notation for open and closed loop robots, Proc. IEEE Int. Conf. on Robotics and Automation, pp. 1174–1180, 1986.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer-Verlag Wien
About this chapter
Cite this chapter
Daemi, M., Heimann, B. (1997). Identification and Compensation of Gear Friction for Modeling of Robots. In: Morecki, A., Bianchi, G., Rzymkowski, C. (eds) ROMANSY 11. International Centre for Mechanical Sciences, vol 381. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2666-0_11
Download citation
DOI: https://doi.org/10.1007/978-3-7091-2666-0_11
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82903-5
Online ISBN: 978-3-7091-2666-0
eBook Packages: Springer Book Archive