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Comparison of two calibration methods for a small industrial robot based on an optical CMM and a laser tracker

Published online by Cambridge University Press:  09 August 2013

Albert Nubiola ,
Mohamed Slamani ,
Ahmed Joubair  and
Ilian A. Bonev
Albert Nubiola
Affiliation:
École de Technologie Supérieure, Montreal, Quebec, Canada
Mohamed Slamani
Affiliation:
École de Technologie Supérieure, Montreal, Quebec, Canada
Ahmed Joubair
Affiliation:
École de Technologie Supérieure, Montreal, Quebec, Canada
Ilian A. Bonev*
Affiliation:
École de Technologie Supérieure, Montreal, Quebec, Canada
*
*Corresponding author. E-mail: ilian.bonev@etsmtl.ca
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Summary

The absolute accuracy of a small industrial robot is improved using a 30-parameter calibration model. The error model takes into account a full kinematic calibration and five compliance parameters related to the stiffness in joints 2, 3, 4, 5, and 6. The linearization of the Jacobian is performed to iteratively find the modeled error parameters. Two coordinate measurement systems are used independently: a laser tracker and an optical CMM. An optimized end-effector is developed specifically for each measurement system. The robot is calibrated using fewer than 50 configurations and the calibration efficiency validated in 1000 configurations using either the laser tracker or the optical CMM. A telescopic ballbar is also used for validation. The results show that the optical CMM yields slightly better results, even when used with the simple triangular plate end-effector that was developed mainly for the laser tracker.

Keywords

Robot calibrationRobot identificationIndustrial robotsAccuracyMetrologyOptical CMMLaser trackerBallbar

Information

Type
Articles
Information
Robotica , Volume 32 , Issue 3 , May 2014 , pp. 447 - 466
Copyright
Copyright © Cambridge University Press 2013 

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References

1.Roth, Z., Mooring, B. and Ravani, B., “An overview of robot calibration,” IEEE J. Robot. Autom. 3 (5), 377–385 (1987).CrossRefGoogle Scholar
2.Besnard, S., Khalil, W. and Garcia, G., “Geometric Calibration of Robotics Using Multiple Plane Constraints,” In: Advances in Robotic Kinematics (Kluwer Academic Publishers, Norwell, MA, 2000) pp. 61–70.Google Scholar
3.Hayati, S. and Mirmirani, M., “Improving the absolute positioning accuracy of robot manipulators,” J. Robot. Syst. 2 (4), 397–413 (1985).CrossRefGoogle Scholar
4.Driels, M., “Using passive end-point motion constraints to calibrate robot manipulators,” J. Dyn. Syst. Meas. Control 115 (3), 560–566 (1993).Google Scholar
5.Juneja, N. and Goldenberg, A., “Kinematic Calibration of a Re-Configurable Robot (RoboTwin),” Proceedings of the 1997 IEEE International Conference on Robotics and Automation (ICRA), Albuquerque, NM, USA (1997) pp. 3178–3183.Google Scholar
6.Beyer, L. and Wulfsberg, J., “Practical robot calibration with ROSY,” Robotica 22 (5), 505–512 (2004).Google Scholar
7.Stone, H. and Sanderson, A., “A Prototype Arm Signature Identification System,” Proceedings of the IEEE International Conference on Robotics and Automation, Raleigh, NC, USA (1987) pp. 175–182.Google Scholar
8.Puskorius, G. and Feldkamp, L., “Global Calibration of a Robot/Vision System,” Proceedings of the 1987 IEEE International Conference on Robotics and Automation, Raleigh, NC, USA (1987) pp. 190–195.Google Scholar
9.Meng, Y. and Zhuang, H., “Self-calibration of camera-equipped robot manipulators,” Int. J. Robot. Res. 20 (11), 909–921 (2001).Google Scholar
10.Dumas, C., Caro, S., Chérif, M., Garnier, S. and Furet, B., “A Methodology for Joint Stiffness Identification of Serial Robots,” Proceedings of the 2010 IEEE International Conference on Intelligent Robots and Systems (2010) pp. 464–469.Google Scholar
11.Nubiola, A. and Bonev, I. A., “Absolute calibration of an ABB IRB 1600 robot using a laser tracker,” Robot. Comput.-Integr. Manuf. 29 (1), 236–245 (2013).Google Scholar
12.Mooring, B. W. and Padavala, S. S., “The Effect of Kinematic Model Complexity on Manipulator Accuracy,” Proceedings of the 1989 IEEE International Conference on Robotics and Automation, Scottsdale, AZ, USA (1989) pp. 593–598.Google Scholar
13.Lightcap, C., Hamner, S., Schmitz, T. and Banks, S., “Improved positioning accuracy of the PA10–6CE robot with geometric and flexibility calibration,” IEEE Trans. Robot. 24 (2), 452–456 (2008).Google Scholar
14.Booschs, F., Schütze, R., Simon, C., Zarzani, F., Wirth, H. and Meier, J., “Increasing the Accuracy of Untaught Robot Positions by Means of a Multi-Camera System,” Proceedings of 2010 International Conference on Indoor Positioning and Indoor Navigation, Zurich, Swtizerland (2010) pp. 15–17.Google Scholar
15.Gatla, C. S., Lumia, R., Wood, J. and Starr, G., “An automated method to calibrate industrial robots using a virtual closed kinematic chain,” IEEE Trans. Robot. 23 (6), 1105–1116 (2007).Google Scholar
16.Borm, J. H. and Meng, C. H., “Determination of optimal measurement configurations for robot calibration based on observability measure,” Int. J. Robot. Res. 10 (1), 51–63 (1991).Google Scholar
17.Driels, M. R. and Pathre, U. S., “Significance of observation strategy on the design of robot calibration experiments,” J. Robot. Syst. 7 (2), 197–223 (1990).Google Scholar
18.Nahvi, A., Hollerbach, J. M. and Hayward, V., “Calibration of a Parallel Robot Using Multiple Kinematic Closed Loops,” Proceedings of the 1994 IEEE International Conference on Robotics and Automation, San Diego, CA, USA (1994) pp. 407–412.Google Scholar
19.Nahvi, A. and Hollerbach, J. M., “The Noise Amplification Index for Optimal Pose Selection in Robot Calibration,” Proceedings of the 1996 IEEE International conference on Robotics and Automation, Minneapolis, MN, USA (1996) pp. 647–654.Google Scholar
20.Zhuang, H. and Roth, Z. S., “Robot calibration using the CPC error model,” Robot. Comput.-Integr. Manuf. 9 (3), 227–237 (1992).Google Scholar
21.Zhuang, H. and Roth, Z. S., “Optimal design of robot accuracy compensators,” IEEE Trans. Robot. Autom. 9 (6), 854–857 (1993).Google Scholar
22.Caenen, J. L. and Angue, J. C., “Identification of Geometric and Nongeometric Parameters of Robots. Robotics and Automation,” Proceedings of the IEEE International Conference on Robotics and Automation, Cincinnati, OH, USA (1990) pp. 1032–1037.Google Scholar
23.Craig, J. J., Introduction to Robotics: Mechanics and Control (Addison-Wesley, Boston, MA, 1986).Google Scholar
24.Sun, Y. and Hollerbach, J. M., “Observability Index Selection for Robot Calibration,” Proceedings of the 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, USA (2008) pp. 831–836.CrossRefGoogle Scholar