Optimal Selection of Measurement Configurations for Stiffness Model Calibration of Anthropomorphic Manipulators

Abstract:

The paper focuses on the calibration of elastostatic parameters of spatial anthropomorphic robots. It proposes a new strategy for optimal selection of the measurement configurations that essentially increases the efficiency of robot calibration. This strategy is based on the concept of the robot test-pose and ensures the best compliance error compensation for the test configuration. The advantages of the proposed approach and its suitability for practical applications are illustrated by numerical examples, which deal with calibration of elastostatic parameters of a 3 degrees of freedom anthropomorphic manipulator with rigid links and compliant actuated joints.

• Periodical: Applied Mechanics and Materials (Volume 162)
• Pages: 161-170
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.162.161
• Online since: March 2012
• Authors: Alexandr Klimchik, Yier Wu, Anatol Pashkevich, Stéphane Caro, Benoît Furet
• Keywords: Anthropomorphic Manipulator, Elastostatic Parameters Identification, Optimality Criteria, Robot Calibration, Selection of Measurement Poses

References

[1] W. Khalil, S. Besnard, Geometric Calibration of Robots with Flexible Joints and Links, Journal of Intelligent and Robotic Systems 34 (2002) 357–379.

[2] F.T. Paziani, B.D. Giacomo, R.H. Tsunaki, Robot measuring form, Robotics and Computer-Integrated Manufacturing 25 (2009) 168-177.

DOI: 10.1016/j.rcim.2007.11.003

[3] A.Y. Elatta, L.P. Gen, F.L. Zhi, Yu Daoyuan and L. Fei, An Overview of Robot Calibration, Information Technology Journal 3 (2004) 74-78.

[4] W.K. Veitchegger, and C.H. Wu, Robot accuracy analysis based on kinematics. IEEE J. Robotics and Automation 2 (1986) 171-179.

[5] Z. Roth, B. Mooring, B. Ravani, An overview of robot calibration, IEEE Journal of Robotics and Automation 3 (1987) 377-385.

DOI: 10.1109/jra.1987.1087124

[6] D.J. Bennett, J.M. Hollerbach, D. Geiger, Autonomous robot calibration for hand-eye coordination, International Journal of Robotics Research 10 (1991) 550-559.

DOI: 10.1177/027836499101000510

[7] W. Khalil, E. Dombre, Modeling, identification and control of robots, Hermes Penton, London, (2002).

[8] D. Daney, N. Andreff, G. Chabert, Y. Papegay, Interval method for calibration of parallel robots: Vision-based experiments, Mechanism and Machine Theory 41 (2006) 929-944.

DOI: 10.1016/j.mechmachtheory.2006.03.014

[9] J. Hollerbach, W. Khalil, M. Gautier, Springer Handbook of robotics, Springer, 2008, Chap. Model identification, pp.321-344.

DOI: 10.1007/978-3-540-30301-5_15

[10] Ch. Gong, J. Yuan, J. Ni, Nongeometric error identification and compensation for robotic system by inverse calibration, Int. J. of Machine Tools & Manufacture 40 (2000) 2119–2137.

DOI: 10.1016/s0890-6955(00)00023-7

[11] I.C. Bogdan, G. Abba: Identification of the servomechanism used for micro-displacement. IROS (2009) 1986-(1991).

[12] A. Pashkevich, A. Klimchik, D. Chablat, Enhanced stiffness modeling of manipulators with passive joints, Mechanism and Machine Theory 46 (2011) 662-679.

DOI: 10.1016/j.mechmachtheory.2010.12.008

[13] R. Ramesh, M.A. Mannan, A.N. Poo, Error compensation in machine tools - a review: Part I: geometric, cutting-force induced and fixture-dependent errors, International Journal of Machine Tools and Manufacture 40 (2000) 1235-1256.

DOI: 10.1016/s0890-6955(00)00009-2

[14] M. Meggiolaro, S. Dubowsky, C. Mavroidis, Geometric and elastic error calibration of a high accuracy patient positioning system, Mechanism and Machine Theory 40 (2005) 415–427.

DOI: 10.1016/j.mechmachtheory.2004.07.013

[15] A. Atkinson, A. Donev, Optimum Experiment Designs. Oxford University Press, (1992).

[16] D. Daney, Optimal measurement configurations for Gough platform calibration. Robotics and Automation, ICRA/ IEEE International Conference (2002) 147-152.

DOI: 10.1109/robot.2002.1013353

[17] D. Daney, Y. Papegay, B. Madeline, Choosing measurement poses for robot calibration with the local convergence method and Tabu search. The International Journal of Robotics Research 24 (2005) 501-518.

DOI: 10.1177/0278364905053185

[18] A. Klimchik, Y. Wu, S. Caro, A. Pashkevich, Design of experiments for calibration of planar anthropomorphic manipulators, AIM (2011) 576-581.

DOI: 10.1109/aim.2011.6027017

[19] H. Zhuang, K. Wang, Z.S. Roth, Optimal selection of measurement configurations for robot calibration using simulated annealing, ICRA (1994) 393-398.

DOI: 10.1109/robot.1994.351264

[20] W. Khalil, M. Gautier, Ch. Enguehard, Identifiable parameters and optimum configurations for robots calibration. Robotica 9 (1991) 63-70.

DOI: 10.1017/s0263574700015575

[21] M.R. Driels1, U.S. Pathre, Significance of observation strategy on the design of robot calibration experiments. Journal of Robotic Systems 7 (1990) 197–223.

DOI: 10.1002/rob.4620070206

[22] Yu Sun and J.M. Hollerbach, Observability index selection for robot calibration. Robotics and Automation, ICRA (2008) 831-836.

DOI: 10.1109/robot.2008.4543308

[23] A. Nahvi, J.M. Hollerbach, The noise amplification index for optimal pose selection in robot calibration. ICRA (1996) 647-654.

DOI: 10.1109/robot.1996.503848

[24] J.H. Borm, C.H. Menq, Determination of optimal measurement configurations for robot calibration based on observability measure. J. of Robotic Systems 10 (1991) 51-63.

DOI: 10.1177/027836499101000106

[25] J. Imoto, Y. Takeda, H. Saito, K. Ichiryu, Optimal kinematic calibration of robots based on maximum positioning-error estimation (Theory and application to a parallel-mechanism pipe bender), Proceedings of the 5th Int. Workshop on Computational Kinematics (2009).

DOI: 10.1007/978-3-642-01947-0_17