Assessing the accuracy of industrial robots through metrology for the enhancement of automated non-destructive testing

Morozov, M. and Riise, J. and Summan, R. and Pierce, S.G. and Mineo, C. and MacLeod, C.N. and Brown, R.H. (2016) Assessing the accuracy of industrial robots through metrology for the enhancement of automated non-destructive testing. In: 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), 2016-09-19 - 2016-09-21, Kongresshaus Baden-Baden. (In Press)

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Abstract

This work presents the study of the accuracy of an industrial robot KR5 arc HW, used to perform quality inspections of components with complex shapes. Metrology techniques such as laser tracking and large volume photogrammetry were deployed to quantify both pose and dynamic path accuracies of the robot in accordance with ISO 9283:1998. The overall positioning pose inaccuracy of the robot is found to be almost 1 mm and path inaccuracy at 100% of the robot rated velocity is 4.5 mm. The maximum pose orientation inaccuracy is found to be 14 degrees and the maximum path orientation inaccuracy is 5 degrees. Despite of the significant maximum inaccuracies, uncertainty of a robotic scanning application is estimated to be 0.5mm. Local positional errors manifest pronounced dependence on the position of the robot end effector in the working envelope. The uncertainties of the measurements are discussed and deemed to be caused by the tool center point calibration, the reference coordinate system transformation and the low accuracy of the photogrammetry system.

ORCID iDs

Morozov, M. ORCID logoORCID: https://orcid.org/0000-0001-7644-8846, Riise, J. ORCID logoORCID: https://orcid.org/0000-0002-5714-4940, Summan, R. ORCID logoORCID: https://orcid.org/0000-0002-4090-4528, Pierce, S.G. ORCID logoORCID: https://orcid.org/0000-0003-0312-8766, Mineo, C. ORCID logoORCID: https://orcid.org/0000-0002-5086-366X, MacLeod, C.N. ORCID logoORCID: https://orcid.org/0000-0003-4364-9769 and Brown, R.H. ORCID logoORCID: https://orcid.org/0000-0001-6310-0728;
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