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Joint stiffness identification of industrial serial robots

Published online by Cambridge University Press:  08 August 2011

Claire Dumas ,
Stéphane Caro ,
Mehdi Cherif ,
Sébastien Garnier  and
Benoît Furet
Claire Dumas*
Affiliation:
Institut de Recherche en Communications et Cybernétique de Nantes, UMR CNRS no 6597, 1 rue de la Noë, 44321 Nantes, France
Stéphane Caro
Affiliation:
Institut de Recherche en Communications et Cybernétique de Nantes, UMR CNRS no 6597, 1 rue de la Noë, 44321 Nantes, France
Mehdi Cherif
Affiliation:
Laboratoire de Génie Mécanique et Matériaux de Bordeaux, 15 rue Naudet CS 10207, 33175 Gradignan Cedex, France
Sébastien Garnier
Affiliation:
Institut de Recherche en Communications et Cybernétique de Nantes, UMR CNRS no 6597, 1 rue de la Noë, 44321 Nantes, France
Benoît Furet
Affiliation:
Institut de Recherche en Communications et Cybernétique de Nantes, UMR CNRS no 6597, 1 rue de la Noë, 44321 Nantes, France
*
*Corresponding author. E-mail: claire.dumas@irccyn.ec-nantes.fr
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Summary

This paper presents a new methodology for the joint stiffness identification of industrial serial robots and as consequence for the evaluation of both translational and rotational displacements of the robot's end-effector subject to an external wrench (force and torque). In this paper, the robot's links are supposed to be quite stiffer than the actuated joints as it is usually the case with industrial serial robots. The robustness of the identification method and the sensitivity of the results to measurement errors, and the number of experimental tests are also analyzed. The Kuka KR240-2 robot is used as an illustrative example throughout the paper.

Keywords

Stiffness analysisJoint stiffness identificationSerial robots
Type
Articles
Information
Robotica , Volume 30 , Issue 4 , July 2012 , pp. 649 - 659
Copyright
Copyright © Cambridge University Press 2011

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References

1.Zha, X. F., “Optimal pose trajectory planning for robot manipulators,” Mech. Mach. Theory 37, 1063–1086 (2002).CrossRefGoogle Scholar
2.Kim, T. and Sarma, S-E., “Toolpath generation along directions of maximum kinematic performance; a first cut at machine-optimal paths,” Comput.-Aided Des. 34, 453–468 (2002).CrossRefGoogle Scholar
3.Matsuoka, S.-I., Shimizu, K., Yamazaki, N. and Oki, Y., “High-speed end milling of an articulated robot and its characteristics,” J. Mater. Process. Technol. 95, 83–89 (1999).CrossRefGoogle Scholar
4.Pan, Z., Zhang, H., Zhu, Z. and Wang, J., “Chatter analysis of robotic machining process,” J. Mater. Process. Technol. 173, 301–309 (2006).CrossRefGoogle Scholar
5.Nagata, F., Hase, T., Haga, Z., Omota, M. and Watanabe, K., “CAD/CAM-based position/force controller for a mold polishing robot,” Mechatronics 17, 207–216 (2007).CrossRefGoogle Scholar
6.Zhang, H., Hang, H., Wang, J., Zhang, G., Gan, Z., Pan, Z., Cui, H. and Zhu, Z., “Machining with Flexible Manipulator: Toward Improving Robotic Machining Performance,” Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Monterey, California, USA (Jul. 24–28, (2005).Google Scholar
7.Nawratil, G., “New performance indices for 6R robots,” Mech. Mach. Theory 42, 1499–1511 (2007).CrossRefGoogle Scholar
8.Kucuk, S. and Bingul, Z., “Comparative study of performance indices for fundamental robot manipulators,” Robot Auton. Syst. 54, 567–573 (2006).CrossRefGoogle Scholar
9.Mansouri, I. and Ouali, M., “A new homogeneous manipulability measure of robot manipulators, based on power concept,” Mechatronics 19, 927–944 (2009).CrossRefGoogle Scholar
10.Kim, B. H., Yi, B. J., Oh, S. R. and Suh, I. H., “Non-dimensionalized performance indices based optimal grasping for multi-fingered hands,” Mechatronics 14, 255–280 (2004).CrossRefGoogle Scholar
11.Dumas, C., Caro, S., Garnier, S. and Furet, B., “Joint stiffness identification of six-revolute industrial serial robots,” Robot. Comput. Integr. Manuf. 27 (4), 881–888 (2011).CrossRefGoogle Scholar
12.Pashkevich, A., Chablat, D. and Wenger, P., “Stiffness analysis of overconstrained parallel manipulators,” Mech. Mach. Theory 44, 966–982 (2009).CrossRefGoogle Scholar
13.Östring, M., Gunnnarsson, S. and Norrlöf, M., “Closed-loop identification of an industrial robot containing flexibilities,” Control Eng. Pract. 11, 291–300 (2009).CrossRefGoogle Scholar
14.Chen, S.-F., “The 6x6 Stiffness Formulation and Transformation of Serial Manipulators via the CCT Theory,” Proceedings of the IEEE International Conference on Robotics and Automation, Taiwan (2003).Google Scholar
15.Alici, G. and Shirinzadeh, B., “Enhanced stiffness modeling, identification and characterization for robot manipulators,” IEEE Trans. Robot. 21 (4), 554–564 (2005).CrossRefGoogle Scholar
16.Chen, S.-F. and Kao, I., “Conservative congruence transformation for joint and cartesian stiffness matrices of robotics hands and fingers,” Int. J. Robot. Res. 19 (9), 835–847 (2000).CrossRefGoogle Scholar
17.Abele, E., Weigold, M. and Rothenbücher, S., “Modeling and identification of an industrial robot for machining applications,” Ann. CIRP, 56 (1), 387–390 (2007).CrossRefGoogle Scholar
18.Pham, M. T., Gautier, M. and Poignet, P., “Identification of Joint Stiffness with Bandpass Filtering,” Proceedings of the 2001 IEEE International Conference on Robotics and Automation, Seoul, Korea (May 21–26, 2001).Google Scholar
19.Khalil, W. and Dombre, E., Modeling, Identification and Control of Robots (Hermes Science Publications, Penton, 2002).Google Scholar
20.Khalil, W. and Creusot, D., “SYMORO+: a system for the symbolic modelling of robots”, Robotica 15, 153–161 (1997).CrossRefGoogle Scholar
21.Merlet, J. P., “Jacobian, manipulability, condition number, and accuracy of parallel robots,” ASME J. Mech. Des. 128, 199–205 (2006).CrossRefGoogle Scholar
22.Caro, S., Binaud, N. and Wenger, P., “Sensitivity analysis of 3-RPR planar parallel manipulators,” ASME J. Mech. Des. 131, 121005-1–121005-13 (2009).CrossRefGoogle Scholar
23.Angeles, J., Fundamentals of Robotic Mechanical Systems Theory, Methods, and Algorithms, 3rd ed. (Springer, New York, 2007) (first edition published in 1997).CrossRefGoogle Scholar
24.Golub, G. H. and Van Loan, C. F., Matrix Computations (The Johns Hopkins University Press, Baltimore, 1989).Google Scholar
25.Li, Z., “Geometrical consideration of robot kinematics,” Int. J. Robot. Autom. 5 (3), 139–145 (1990).Google Scholar
26.Paden, B. and Sastry, S., “Optimal kinematic design of 6R manipulator,” Int. J. Robot. Res. 7 (2), 43–61 (1988).CrossRefGoogle Scholar
27.Ranjbaran, F., Angeles, J., Gonzalez-Palacios, M. A. and Patel, R. V., “The mechanical design of a seven-axes manipulator with kinematic isotropy,” ASME J. Intell. Robot. Syst. 14 (1), 21–41 (1995).CrossRefGoogle Scholar
28.Khan, W.A. and Angeles, J., “The kinetostatic optimization of robotic manipulators: The inverse and the direct problems,” ASME J. Mech. Des. 128, 168–178 (2006).CrossRefGoogle Scholar
29.www.faro.comGoogle Scholar