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Journal of Robotics
Volume 2012, Article ID 376293, 9 pages
Research Article

Fuzzy Interpolation and Other Interpolation Methods Used in Robot Calibrations

1Johnson C. Smith University, Charlotte, NC 28216, USA
2Benedict College, Columbia, SC 29204, USA
3Georgia Gwinnett College, Atlanta, GA 30043, USA

Received 8 September 2011; Revised 4 February 2012; Accepted 6 February 2012

Academic Editor: G. Muscato

Copyright © 2012 Ying Bai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A novel interpolation algorithm, fuzzy interpolation, is presented and compared with other popular interpolation methods widely implemented in industrial robots calibrations and manufacturing applications. Different interpolation algorithms have been developed, reported, and implemented in many industrial robot calibrations and manufacturing processes in recent years. Most of them are based on looking for the optimal interpolation trajectories based on some known values on given points around a workspace. However, it is rare to build an optimal interpolation results based on some random noises, and this is one of the most popular topics in industrial testing and measurement applications. The fuzzy interpolation algorithm (FIA) reported in this paper provides a convenient and simple way to solve this problem and offers more accurate interpolation results based on given position or orientation errors that are randomly distributed in real time. This method can be implemented in many industrial applications, such as manipulators measurements and calibrations, industrial automations, and semiconductor manufacturing processes.