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Unconventional calibration strategies for micromanipulation work-cells

Published online by Cambridge University Press:  20 August 2018

G. Fontana Open the ORCID record for G. Fontana [Opens in a new window] ,
S. Ruggeri Open the ORCID record for S. Ruggeri [Opens in a new window] ,
G. Legnani Open the ORCID record for G. Legnani [Opens in a new window]  and
I. Fassi Open the ORCID record for I. Fassi [Opens in a new window]
G. Fontana*
Affiliation:
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, 20133 Milan, Italy. Emails: [email protected], [email protected], [email protected]
S. Ruggeri
Affiliation:
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, 20133 Milan, Italy. Emails: [email protected], [email protected], [email protected]
G. Legnani
Affiliation:
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, 20133 Milan, Italy. Emails: [email protected], [email protected], [email protected] Department of Mechanical and Industrial Engineering, University of Brescia, 25123 Brescia, Italy
I. Fassi
Affiliation:
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, 20133 Milan, Italy. Emails: [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper presents and compares a set of calibration strategies useful to calibrate vision-based robotised work-cells for micromanipulation and microassembly. To grasp and release microparts precisely, robot calibration, camera calibration and robot-camera registration are needed. Conventional calibration methods are very onerous at the microscale, therefore, two alternative unconventional procedures, called virtual grid calibration and hybrid calibration, are developed for work-cells with high-performance robots, minimising necessary instrumentation. Moreover, an effective calibration of the robot end-effector is designed to compensate for misalignment and orientation errors with respect to the vertical rotational axis. This paper describes the calibration methods and their implementation, the results and the improvements achieved. A detailed comparison between the hybrid and the virtual grid calibrations is provided, demonstrating the higher performance of the latter strategy.

Keywords

MicromanipulationCalibrationCamera calibrationWork-cell accuracy2D vision systems
Type
Articles
Information
Robotica , Volume 36 , Issue 12 , December 2018 , pp. 1897 - 1919
Copyright
Copyright © Cambridge University Press 2018 

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References

1. Cecil, J., Bharathi Raj Kumar, M. B., Lu, Y. and Basallali, V., “A review of micro-devices assembly techniques and technology,” Int. J. Adv. Manuf. Technol. 83 (9), 1569–1581 (2016).Google Scholar
2. Schröer, K., “Precision and Calibration,” In: Handbook of Industrial Robotics, 2nd ed. (Nof, S. Y. ed.) (Wiley & Sons Inc., New York, 1999) pp. 795–810.Google Scholar
3. Legnani, G., Mina, C. and Trevelyan, J., “Static calibration of industrial manipulators: Design of an optical instrumentation and application to SCARA robots,” J. Robot. Syst. 13 (7), 445–460 (1996).Google Scholar
4. Omodei, A., Legnani, G. and Adamini, R., “Calibration of a measuring robot: Experimental results on a 5 DOF structure,” J. Robot. Syst. 18 (5), 237–250 (2001).Google Scholar
5. Mooring, B. W., Roth, Z. S. and Driels, M. R., Fundamentals of Manipulator Calibration (John Wiley & Sons, Inc, New York, 1991).Google Scholar
6. Zhang, Z., “A flexible new technique for camera calibration,” IEEE Trans. Pattern Anal. Mach. Intell. 22 (11), 1330–1334 (2000).Google Scholar
7. Fryer, J. G. and Brown, D. C., “Lens distortion for close-range photogrammetry,” Photogramm. Eng. Remote Sens. 52, 51–58 (1986).Google Scholar
8. Ruggeri, S., Fontana, G. and Fassi, I., “Chapter 9: Micro-assembly,” In: Micro-Manufacturing Technologies and Their Applications: A Theoretical and Practical Guide (Fassi, I. and Shipley, D. eds.) (Springer International Publishing, 2017) pp. 223–259.Google Scholar
9. Fontana, G., “Assembly at the Microscale: Design and Implementation of a Robotised Work-Cell,” Ph.D. Thesis (University of Brescia, 2014).Google Scholar
10. Ruggeri, S., Advanced Robotic Applications: Performance Improvement Techniques for Industrial Robots Acting at the Macro- and Micro-Scale (Scholar's Press, Germany, 2013) pp. 177–240.Google Scholar
11. Mitsubishi website: http://www.mitsubishi-automation.co.uk/.Google Scholar
12. Bottema, O. and Roth, B., Theoretical Kinematics (Dover Publications Inc., New York, 1979) pp. 312–315.Google Scholar
13. Legnani, G., Gabrielli, A., Ousdad, A., Fassi, I., Ruggeri, S. and Fontana, G., “A Laser Calibration Device for Mini Robots,” Proceedings of the ASME 2015 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2015, Boston, Massachusetts, USA (2015).Google Scholar
14. ISO 9283:1998, “Manipulating industrial robots - Performance criteria and related test methods,” 2nd Edition (www.iso.org, International Organization for Standardization, Geneva, Switzerland, 1998) pp. 1–60. Technical Committee: ISO/TC 299 Robotics. ICS: 25.040.30 Industrial robots. Manipulators.Google Scholar
15. ISO/TR 13309:1995, “Manipulating industrial robots - Informative guide on test equipment and metrology methods of operation for robot performance evaluation in accordance with ISO 9283,” (1995), 1st Edition (www.iso.org, International Organization for Standardization, Geneva, Switzerland, 1995), pp. 1–15. Technical Committee: ISO/TC 299 Robotics. ICS: 25.040.30 Industrial robots. Manipulators.Google Scholar
16. Tamadazte, B., Dembélé, S. and Le Fort-Piat, N., “A multiscale calibration of a photon videomicroscope for visual servo control: Application to MEMS micromanipulation and microassembly,” Sensors & Transducers J. 5(Special Issue), 37–52 (2009).Google Scholar
17. Bradski, G. and Kaehler, A., “Chapter 11: Camera Models and Calibration,” In: Learning OpenCV (Loukides, M. ed.) (O'Reilly Media, Inc., Sebastopol CA, USA, 2008) pp. 370–404.Google Scholar
18. Fassi, I. and Legnani, G., “Hand to sensor calibration: A geometrical interpretation of the matrix equation AX=XB,” J. Robot. Syst. 22 (9), 497–506 (2005).Google Scholar
19. Fassi, I., Legnani, G., Tosi, D. and Omodei, A., “Chapter 8: Calibration of Serial Manipulators: Theory and Applications,” In: Industrial Robotics: Programming, Simulation and Applications (Huat, L. K. ed.) (Intech, Book, 2006).Google Scholar
20. Legnani, G., Tosi, D., Adamini, R. and Fassi, I., “Chapter 9: Calibration of Parallel Kinematic Machines: Theory and Applications,” In: Industrial Robotics: Programming, Simulation and Applications (Huat, L. K. ed.) (Intech, Book, 2006).Google Scholar
21. Shapiro, L. G. and Stockman, G. C., Computer Vision (Prentice-Hall, Englewood Cliffs, NJ, 2002).Google Scholar