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Article

Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers

Department of Engineering Sciences, University of Agder, 4879 Grimstad, Norway
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Author to whom correspondence should be addressed.
Sensors 2019, 19(7), 1561; https://doi.org/10.3390/s19071561
Received: 21 December 2018 / Revised: 23 February 2019 / Accepted: 26 March 2019 / Published: 31 March 2019
(This article belongs to the Special Issue Depth Sensors and 3D Vision)
This paper describes a non-invasive, automatic, and robust method for calibrating a scalable RGB-D sensor network based on retroreflective ArUco markers and the iterative closest point (ICP) scheme. We demonstrate the system by calibrating a sensor network comprised of six sensor nodes positioned in a relatively large industrial robot cell with an approximate size of 10   m × 10   m × 4 m . Here, the automatic calibration achieved an average Euclidean error of 3 c m at distances up to 9.45 m . To achieve robustness, we apply several innovative techniques: Firstly, we mitigate the ambiguity problem that occurs when detecting a marker at long range or low resolution by comparing the camera projection with depth data. Secondly, we use retroreflective fiducial markers in the RGB-D calibration for improved accuracy and detectability. Finally, the repeating ICP refinement uses an exact region of interest such that we employ the precise depth measurements of the retroreflective surfaces only. The complete calibration software and a recorded dataset are publically available and open source. View Full-Text
Keywords: 3D sensors; time-of-flight; automatic calibration; retroreflective markers; ambiguity problem 3D sensors; time-of-flight; automatic calibration; retroreflective markers; ambiguity problem
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  • Externally hosted supplementary file 1
    Doi: 10.5281/zenodo.2554030
    Link: https://doi.org/10.5281/zenodo.2554030
    Description: Calibration software. This release documents the software state as used for the results presented in the paper "Automatic Calibration of an Industrial RGB-D Camera Network using Retroreflective Fiducial Markers."
MDPI and ACS Style

Aalerud, A.; Dybedal, J.; Hovland, G. Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers. Sensors 2019, 19, 1561. https://doi.org/10.3390/s19071561

AMA Style

Aalerud A, Dybedal J, Hovland G. Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers. Sensors. 2019; 19(7):1561. https://doi.org/10.3390/s19071561

Chicago/Turabian Style

Aalerud, Atle, Joacim Dybedal, and Geir Hovland. 2019. "Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers" Sensors 19, no. 7: 1561. https://doi.org/10.3390/s19071561

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