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Sensors 2018, 18(1), 197; https://doi.org/10.3390/s18010197

Effective Data-Driven Calibration for a Galvanometric Laser Scanning System Using Binocular Stereo Vision

College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China
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Received: 28 October 2017 / Revised: 4 January 2018 / Accepted: 8 January 2018 / Published: 12 January 2018
(This article belongs to the Section Physical Sensors)
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Abstract

A new solution to the problem of galvanometric laser scanning (GLS) system calibration is presented. Under the machine learning framework, we build a single-hidden layer feedforward neural network (SLFN)to represent the GLS system, which takes the digital control signal at the drives of the GLS system as input and the space vector of the corresponding outgoing laser beam as output. The training data set is obtained with the aid of a moving mechanism and a binocular stereo system. The parameters of the SLFN are efficiently solved in a closed form by using extreme learning machine (ELM). By quantitatively analyzing the regression precision with respective to the number of hidden neurons in the SLFN, we demonstrate that the proper number of hidden neurons can be safely chosen from a broad interval to guarantee good generalization performance. Compared to the traditional model-driven calibration, the proposed calibration method does not need a complex modeling process and is more accurate and stable. As the output of the network is the space vectors of the outgoing laser beams, it costs much less training time and can provide a uniform solution to both laser projection and 3D-reconstruction, in contrast with the existing data-driven calibration method which only works for the laser triangulation problem. Calibration experiment, projection experiment and 3D reconstruction experiment are respectively conducted to test the proposed method, and good results are obtained. View Full-Text
Keywords: galvanometric laser scanners; calibration; ELM; SLFN; laser projection; 3D laser measurement galvanometric laser scanners; calibration; ELM; SLFN; laser projection; 3D laser measurement
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Tu, J.; Zhang, L. Effective Data-Driven Calibration for a Galvanometric Laser Scanning System Using Binocular Stereo Vision. Sensors 2018, 18, 197.

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