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Open AccessArticle

Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner

by Chengyi Yu 1, Xiaobo Chen 1 and Juntong Xi 1,2,*
1
State Key Laboratory of Mechanical System and Vibration, Shanghai Jiaotong University, Shanghai 200240, China
2
Shanghai Key Laboratory of Advanced Manufacturing Environment, Shanghai 200030, China
*
Author to whom correspondence should be addressed.
Academic Editor: Thierry Bosch
Sensors 2017, 17(1), 164; https://doi.org/10.3390/s17010164
Received: 19 October 2016 / Revised: 10 January 2017 / Accepted: 12 January 2017 / Published: 15 January 2017
A laser stripe sensor has limited application when a point cloud of geometric samples on the surface of the object needs to be collected, so a galvanometric laser scanner is designed by using a one-mirror galvanometer element as its mechanical device to drive the laser stripe to sweep along the object. A novel mathematical model is derived for the proposed galvanometer laser scanner without any position assumptions and then a model-driven calibration procedure is proposed. Compared with available model-driven approaches, the influence of machining and assembly errors is considered in the proposed model. Meanwhile, a plane-constraint-based approach is proposed to extract a large number of calibration points effectively and accurately to calibrate the galvanometric laser scanner. Repeatability and accuracy of the galvanometric laser scanner are evaluated on the automobile production line to verify the efficiency and accuracy of the proposed calibration method. Experimental results show that the proposed calibration approach yields similar measurement performance compared with a look-up table calibration method. View Full-Text
Keywords: galvanometric laser scanner; calibration; the screw theory; laser stripe sensor galvanometric laser scanner; calibration; the screw theory; laser stripe sensor
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MDPI and ACS Style

Yu, C.; Chen, X.; Xi, J. Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner. Sensors 2017, 17, 164.

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