Reducing Localization Error of Vision-Guided Industrial Robots
Marek Franaszek, Geraldine S. Cheok, Jeremy A. Marvel
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.
2019 IEEE International Symposium on RObotic and SEnsors Environments (ROSE). ROSE 2019
, Cheok, G.
and Marvel, J.
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 December 8, 2023)