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 October 10, 2024)
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Reducing Localization Error of Vision-Guided Industrial Robots
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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
Pub Type
Conferences
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Keywords
robot localization error, hand-eye calibration, rigid-body registration, volumetric error compensation, accuracy, repeatability
Citation
Issues
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Created June 18, 2019, Updated February 3, 2020