Abstract
This paper addresses challenges of parameter estimation of an arbitrary object which is manipulated by an underactuated handling system. In the present scenario, a robot is extended with a passive orientation device. Since the passive joints are steered by energy control, knowledge of the inertial parameters of the gripped object must be obtained. For this purpose, an evaluation process is shown to find excitation inputs that are based on normal operation motion profiles. The general applicability of the excitation is then demonstrated along with an optimization to improve the excitation of the passive joints which yields a better estimation. Since it is difficult to obtain acceleration signals, the influence of their accuracy on the estimates is additionally illustrated. The article closes with the identification of future developments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
1. Borchert, G., Raatz, A., 2016, A new method for combining handling systems with passive orientation devices, In: CIRP Annals - Manufacturing Technology, Elsevier B.V., 2016, Vol. 65/1, pp. 49-52.
2. Fanuc Robotics America Corporation. Datasheet: FANUC Robot M-3iA. FRA-24/02/2014, Online available via: www.fanucrobotics.com [cited on 14.07.15].
3. Liu, N., Wu, J., 2014, Kinematics and Application of a Hybrid Industrial Robot - Delta-RST, In: Sensors&Transducers, Vol. 169/4, April 2014, pp. 186-192.
4. Borchert, G., Raatz, A., 2015, An Analysis Process to Improve the Mobility of a Parallel Robot for Assembly Tasks, 14thWorld Congress in Mechanism and Machine Science, 25-30 Oct., 2015, Taipei, Taiwan.
5. Astroem, K.-J., Furuta, K., 2000, Swinging up a pendulum by energy control, Journal Automatica, 36/2:287-295.
6. De Luca, A., Iannitti, S., Mattone, R., Oriolo, G., 2002, Underactuated manipulators: Control properties and techniques, Machine Intelligence and Robotic Control, Vol. 4/3, pp. 113-125.
7. Marini, F., Walczak, B., 2015, Particle swarm optimization (PSO). A tutorial, In: Chemometrics and Intelligent Laboratory Systems, Vol. 149, Part B, 15 December 2015, pp. 153-165.
8. Gautier, M., Khalil, W., 1991, Exciting Trajectories for the Identification of Base Inertial Parameters of Robots, In: Proc. of the 30th Conference on Decision and Control, Brighton, England, Dec., 1991, pp. 494-499.
9. Isermann, R., 2008, Mechatronische Systeme. Grundlagen, Springer Berlin Heidelberg, 2008, DOI 10.1007/978-3-540-32512-3
10. Siciliano, B., Khatib, O., 2008, Springer Handbook of Robotics, Springer Berlin Heidelberg, 2008, DOI 10.1007/978-3-540-30301-5
11. Lawson, C.L., Hanson, R.J., 1995, Solving Least Squares Problems, Philadelphia: SIAM, c1995, ISBN-13: 978-0898713565
12. Isermann, R., 1988, Identifikation dynamischer Systeme 1: Grundlegende Methoden, Springer Berlin Heidelberg, 1992, DOI 10.1007/978-3-642-84679-3
13. Nelles, O., 2001, Nonlinear System Identification, Springer Berlin Heidelberg, 2001, DOI 10.1007/978-3-662-04323-3
14. Biagotti, L., Melchiorri, C. (2008): Trajectory Planning for Automatic Ma-chines and Robots, ISBN: 978-3-540-85628-3.
15. Bergerman, M., Lee, C., Xu, Y., 1995, Dynamic Coupling of underactuated Manipulators, In: Proc. of the 4th IEEE Conference on Control Applications, Albany, USA, Sep. 1995, pp. 500-505.
16. Allgöver, F., Gilles, E.D., 1993, Nichtlinearer Reglerentwurf auf der Grundlage exakter Linearisierungstechniken, VDI Berichte Nr. 1026, 1993, pp. 209-234.
17. Sun, Y., Hollerbach, M., 2008, Observability Index Selection for Robot Calibration, In: IEEE Int. Conference on Robotics and Automation, Pasadena, USA, May 19-23, 2008, pp. 831-836.
18. Gautier, M., 1992, Optimal Motion Planning For Robots Inertial Parameters Identification, In: Proc. of Decision and Control, 16-18 Dec., Tucson, 1992, pp. 70-73.
19. Gautier, M., Khalil, W., 1992, Exciting Trajectories for the Identification of Base Inertial Parameters of Robots, In: The Int. Journal of Robotics Research, Vol. 11/4, Aug., 1992, pp. 362-375.
20. Schroer, K., 1993, Theory of kinematic modelling and numerical procedures for robot calibration, In: Robot Calibration, ed. by R. Bernhardt, S.L. Albright (Chapman Hall, London 1993), pp. 157-196.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer-Verlag GmbH Deutschland
About this paper
Cite this paper
Borchert, G., Diekmeyer, J., Bild, K., Raatz, A. (2017). Normal Operation Input Signals for Parameter Estimation in Underactuated Structures. In: Schüppstuhl, T., Franke, J., Tracht, K. (eds) Tagungsband des 2. Kongresses Montage Handhabung Industrieroboter. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54441-9_5
Download citation
DOI: https://doi.org/10.1007/978-3-662-54441-9_5
Published:
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-54440-2
Online ISBN: 978-3-662-54441-9
eBook Packages: Computer Science and Engineering (German Language)