Hostname: page-component-6b989bf9dc-vmcqm Total loading time: 0 Render date: 2024-04-13T17:17:14.968Z Has data issue: false hasContentIssue false

A one-step calibration method without redundant parameters for a laser stripe sensor

Published online by Cambridge University Press:  08 January 2024

Yang Mao
Affiliation:
School of Mechanical and Automation Engineering, Shanghai Institute of Technology, Shanghai, China
Yu He
Affiliation:
School of Mechanical and Automation Engineering, Shanghai Institute of Technology, Shanghai, China
Chengyi Yu
Affiliation:
Shanghai Satellite Equipment Research Institute, Shanghai, China
Honghui Zhang
Affiliation:
Shanghai Platform for Smart Manufacturing, Shanghai, China
Ke Zhang*
Affiliation:
School of Mechanical and Automation Engineering, Shanghai Institute of Technology, Shanghai, China
Xiaojun Sun
Affiliation:
Shanghai Waigaoqiao Shipbuilding Co., Ltd., Shanghai, China
*
Corresponding author: Ke Zhang; Email: zkwy2004@126.com

Abstract

A laser stripe sensor has two kinds of calibration methods. One is based on the homography model between the laser stripe plane and the image plane, which is called the one-step calibration method. The other is based on the simple triangular method, which is named as the two-step calibration method. However, the geometrical meaning of each element in the one-step calibration method is not clear as that in the two-step calibration method. A novel mathematical derivation is presented to reveal the geometrical meaning of each parameter in the one-step calibration method, and then the comparative study of the one-step calibration method and the two-step calibration method is completed and the intrinsic relationship is derived. What is more, a one-step calibration method is proposed with 7 independent parameters rather than 11 independent parameters. Experiments are conducted to verify the accuracy and robust of the proposed calibration method.

Type
Research Article
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abu-Nabah, BA, Elsoussi, AO and Alami, AA (2016) Simple laser vision sensor calibration for surface profiling applications. Optics & Lasers in Engineering 84, 5161.CrossRefGoogle Scholar
Baeg, MH, Baeg, SH, Moon, C, Jeong, GM, Ahn, HS and Kim, DH (2008) A new robotic 3D inspection system of automotive screw hole. International Journal of Control Automation & Systems 6, 740745.Google Scholar
Chen, C and Kak, A (1987) Modeling and calibration of a structured light scanner for 3-D robot vision. Proceedings 1987 IEEE International Conference on Robotics and Automation, Vol. 4. IEEE, pp. 807815.CrossRefGoogle Scholar
Dewar, R (1988) Self-generated Targets for Spatial Calibration of Structured-Light Optical Sectioning Sensors with Respect to an External Coordinate System. Pittsburgh: Society of Manufacturing Engineers.Google Scholar
Duan, F (2000) A new accurate method for the calibration of line structured light sensor. Chinese Journal of Scientific Instrument 1, 108110.Google Scholar
Forest Collado, J (2004) New Methods for Triangulation-Based Shape Acquisition Using Laser Scanners. Catalonia Autonomous Region, Spain: Universitat de Girona.Google Scholar
Gan, Z and Tang, Q (2011) Visual Sensing and Its Applications: integration of Laser Sensors to Industrial Robots. Zhejiang, China: Zhejiang University Press, Springer.CrossRefGoogle Scholar
Heikkila, J and Silven, O (1997) A four-step camera calibration procedure with implicit image correction. IEEE Computer Society Conference on Computer Vision & Pattern Recognition, pp. 11061112.CrossRefGoogle Scholar
Huang, W and Kovacevic, R (2011) A laser-based vision system for weld quality inspection. Sensors (Basel) 11, 506521.CrossRefGoogle ScholarPubMed
Huynh, DQ, Owens, RA and Hartmann, P (1999) Calibrating a structured light stripe system: a novel approach. International Journal of Computer Vision 33, 7386.CrossRefGoogle Scholar
Irandoust, M, Emam, SM and Ansari, MA (2022) Measurement accuracy assessment of the 3D laser triangulation scanner based on the iso-disparity surfaces. Journal of the Brazilian Society of Mechanical Sciences and Engineering 44, 164176.CrossRefGoogle Scholar
Jia, NN, Li, ZY, Ren, JL, Wang, YJ and Yang, LQ (2019) A 3D reconstruction method based on grid laser and gray scale photo for visual inspection of welds. Optics and Laser Technology 119, 105648.CrossRefGoogle Scholar
Joubair, A and Bonev, IA (2014) Kinematic calibration of a six-axis serial robot using distance and sphere constraints. International Journal of Advanced Manufacturing Technology 77, 515523.CrossRefGoogle Scholar
Li, J, Zhu, J, Duan, K, Tang, Q, Wang, Y, Guo, Y and Lin, X (2008) Calibration of a portable laser 3-D scanner used by a robot and its use in measurement. Optical Engineering 47, 017202-017202-017208.CrossRefGoogle Scholar
Luo, HF, Xu, J, Binh, NH, Liu, ST, Zhang, C and Chen, K (2014) A simple calibration procedure for structured light system. Optics and Lasers in Engineering 57, 612.CrossRefGoogle Scholar
Mao, Y, Zeng, L, Jiang, J and Yu, C (2018) Plane-constraint-based calibration method for a galvanometric laser scanner. Advances in Mechanical Engineering 10, 1687814018773670.CrossRefGoogle Scholar
Niola, V, Rossi, C, Savino, S and Strano, S (2011) A method for the calibration of a 3-D laser scanner. Robotics and Computer-Integrated Manufacturing 27, 479484.CrossRefGoogle Scholar
Tsai, RY (1987) A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal of Robotics & Automation 3, 323344.CrossRefGoogle Scholar
Wei, ZZ, Zhang, GJ and Xu, Y (2003) Calibration approach for structured-light-stripe vision sensor based on the invariance of double cross-ratio. Optical Engineering 42, 29562966.CrossRefGoogle Scholar
Xie, Z, Wang, X and Chi, S (2014) Simultaneous calibration of the intrinsic and extrinsic parameters of structured-light sensors. Optics and Lasers in Engineering 58, 918.CrossRefGoogle Scholar
Xu, G, Liu, L, Zeng, J and Shi, D (1995) A new method of calibration in 3D vision system based on structure-light. Chinese Journal of Computers 6, 450456.Google Scholar
Yang, L, Liu, YH and Peng, JZ (2020) Advances techniques of the structured light sensing in intelligent welding robots: a review. International Journal of Advanced Manufacturing Technology 110, 10271046.CrossRefGoogle Scholar
Yi, S and Min, S (2021) A practical calibration method for stripe laser imaging system. IEEE Transactions on Instrumentation and Measurement 110, 10271046.Google Scholar
Yu, CY, Chen, XB and Xi, JT (2017) Modeling and calibration of a novel one-mirror galvanometric laser scanner. Sensors 17, 164177.CrossRefGoogle ScholarPubMed
Zhang, Z (2000) A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis & Machine Intelligence 22, 13301334.CrossRefGoogle Scholar
Zhang, L, Wu, CY and Zou, YY (2009) An on-line visual seam tracking sensor system during laser beam welding. Itcs: 2009 International Conference on Information Technology and Computer Science, Proceedings, Vol 2, Proceedings, pp. 361364.CrossRefGoogle Scholar
Zhou, FQ, Zhang, GJ and Jiang, J (2005) Constructing feature points for calibrating a structured light vision sensor by viewing a plane from unknown orientations. Optics and Lasers in Engineering 43, 10561070.CrossRefGoogle Scholar