An Improved Calibration Algorithm for Low-Cost Laser Triangulation-Based Sensor

Liu Lin; Yong Ting Zhao; Zi Cheng Qiu

doi:10.4028/www.scientific.net/AMR.998-999.569

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 998-999An Improved Calibration Algorithm for Low-Cost...

An Improved Calibration Algorithm for Low-Cost Laser Triangulation-Based Sensor

Abstract:

The key to decide range accuracy in the low-cost laser triangulation-based system is the calibration of structural parameters. According to the problem that the curve fitting based on Least Square Method cannot accurately determine parameters in the case of not knowing the range of parameters, an improve algorithm is proposed for simplifying mathematical model and determining the range of the parameters.

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Periodical:

Advanced Materials Research (Volumes 998-999)

Pages:

569-573

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.998-999.569

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Online since:

July 2014

Authors:

Liu Lin*, Yong Ting Zhao, Zi Cheng Qiu

Keywords:

Calibration Algorithm, Laser Range Sensor, Triangulation

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* - Corresponding Author

References

[1] F.J. Pipitone, T.G. Marshall, A wide-field scanning triangulation rangefinder for machine vision, The International journal of robotics research, 2 (1983) 39-49.

DOI: 10.1177/027836498300200104

Google Scholar

[2] E.L. Hall, J.B. Tio, C.A. McPherson, F.A. Sadjadi, Measuring curved surfaces for robot vision, Computer, 15 (1982) 42-54.

DOI: 10.1109/mc.1982.1653915

Google Scholar

[3] F. Blais, Review of 20 years of range sensor development, Journal of Electronic Imaging, 13 (2004).

Google Scholar

[4] F. De Nisi, F. Comper, L. Gonzo, M. Gottardi, D. Stoppa, A. Simoni, J. -A. Beraldin, A CMOS sensor optimized for laser spot-position detection, Sensors Journal, IEEE, 5 (2005) 1296-1304.

DOI: 10.1109/jsen.2005.859217

Google Scholar

[5] T. Borangiu, A. Dogar, A. Dumitrache, Modeling and Simulation of Short Range 3D Triangulation-Based Laser Scanning System, International Journal of Computers, Communications & Control, 3 (2008).

Google Scholar

[6] B. Yamauchi, Frontier-based exploration using multiple robots, Proceedings of the second international conference on Autonomous agents, ACM, 1998, pp.47-53.

DOI: 10.1145/280765.280773

Google Scholar

[7] K. Konolige, J. Augenbraun, N. Donaldson, C. Fiebig, P. Shah, A low-cost laser distance sensor, Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on, IEEE, 2008, pp.3002-3008.

DOI: 10.1109/robot.2008.4543666

Google Scholar

[8] P.J. Besl, Active, optical range imaging sensors, Machine vision and applications, 1 (1988) 127-152.

DOI: 10.1007/bf01212277

Google Scholar

[9] Z. Zhang, A flexible new technique for camera calibration, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 22 (2000) 1330-1334.

DOI: 10.1109/34.888718

Google Scholar

[10] R. Fisher, D. Naidu, A comparison of algorithms for subpixel peak detection, Image Technology, Springer1996, pp.385-404.

DOI: 10.1007/978-3-642-58288-2_15

Google Scholar