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Reducing Localization Error of Vision-Guided Industrial Robots

Published

Author(s)

Marek Franaszek, Geraldine S. Cheok, Jeremy A. Marvel

Abstract

In many manufacturing applications, such as automated drilling or inspection of large parts, accurate knowledge of both position and orientation is critical. In this paper, a method for reducing robot end-effector position and orientation error is presented. Experimental results show that the method can reduce the median position error by 97% (to 0.3 mm) and the median orientation error by 57% (to 0.27 deg). Limitations of the method caused by the hand-eye calibration are discussed.
Proceedings Title
2019 IEEE International Symposium on RObotic and SEnsors Environments (ROSE). ROSE 2019
Conference Dates
June 17-18, 2019
Conference Location
Ottawa

Keywords

robot localization error, hand-eye calibration, rigid-body registration, volumetric error compensation, accuracy, repeatability

Citation

Franaszek, M. , Cheok, G. and Marvel, J. (2019), Reducing Localization Error of Vision-Guided Industrial Robots, 2019 IEEE International Symposium on RObotic and SEnsors Environments (ROSE). ROSE 2019, Ottawa, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927534 (Accessed September 27, 2021)
Created June 18, 2019, Updated February 3, 2020