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RGB-D and Lidar Calibration Supported by GPU

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Computer Vision and Graphics (ICCVG 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12334))

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Abstract

There can be observed a constant increase in the number of sensors used in computer vision systems. This affects especially mobile robots designed to operate in crowded environment. Such robots are commonly equipped with a wide range of depths sensors like Lidars and RGB-D cameras. The sensors must be properly calibrated and their reference frames aligned. This paper presents a calibration procedure for Lidars and RGB-D sensors. A simple inflated ball is used as a calibration pattern. The method applies RanSaC algorithm for pattern detection. The detected sphere centroids are then aligned to estimate rigid transformation between sensors. In addition, an improved GPU RanSaC procedure together with color filtering for RGB-D sensors is used for increased efficiency. The experiments show that this basic calibration setup offers accuracies comparable to those reported in literature. There is also demonstrated a significant speedup due to utilization of GPU-supported procedures as well as proposed color prefiltering.

The research was supported by the United Robots company under a NCBiR grant POIR.01.01.01-00-0206/17.

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References

  1. Arun, K.S., Huang, T.S., Blostein, S.D.: Least-squares fitting of two 3-D point sets. IEEE Trans. Pattern Anal. Mach. Intell. PAMI 9(5), 698–700 (1987)

    Article  Google Scholar 

  2. Debattisti, S., Mazzei, L., Panciroli, M.: Automated extrinsic laser and camera inter-calibration using triangular targets. In: 2013 IEEE Intelligent Vehicles Symposium (IV), pp. 696–701 (2013)

    Google Scholar 

  3. Fernandez-Rordiguez, S., Wedekind, J.: Recognition of 2D-objects using RANSAC. Technical report, Sheffield Hallam University, January 2008

    Google Scholar 

  4. Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981). https://doi.org/10.1145/358669.358692

    Article  MathSciNet  Google Scholar 

  5. Geiger, A., Moosmann, F., Car, Ö., Schuster, B.: Automatic camera and range sensor calibration using a single shot. In: 2012 IEEE International Conference on Robotics and Automation, pp. 3936–3943 (2012)

    Google Scholar 

  6. Guindel, C., Beltrán, J., Martín, D., García, F.: Automatic extrinsic calibration for lidar-stereo vehicle sensor setups. In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), pp. 1–6 (2017)

    Google Scholar 

  7. Hasting, G., Rubin, A.: Colour spaces - a review of historic and modern colour models*. African Vis. Eye Health 71 (2012). https://doi.org/10.4102/aveh.v71i3.76

  8. Levenberg, K.: A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. 2(2), 164–168 (1944). http://www.jstor.org/stable/43633451

    Article  MathSciNet  MATH  Google Scholar 

  9. Marquardt, D.W.: An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11(2), 431–441 (1963). https://doi.org/10.1137/0111030

    Article  MathSciNet  MATH  Google Scholar 

  10. Moghadam, P., Bosse, M., Zlot, R.: Line-based extrinsic calibration of range and image sensors. In: 2013 IEEE International Conference on Robotics and Automation, pp. 3685–3691 (2013)

    Google Scholar 

  11. Park, Y., Yun, S., Won, C., Cho, K., Um, K., Sim, S.: Calibration between color camera and 3D lidar instruments with a polygonal planar board. Sensors (Basel, Switzerland) 14, 5333–5353 (2014). https://doi.org/10.3390/s140305333

  12. Pereira, M., Silva, D., Santos, V., Dias, P.: Self calibration of multiple lidars and cameras on autonomous vehicles. Robot. Auton. Syst. 83 (2016). https://doi.org/10.1016/j.robot.2016.05.010

  13. Quigley, M., et al.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3, January 2009

    Google Scholar 

  14. Ros approximate time synchronization filter. http://wiki.ros.org/message_filters/ApproximateTime. Accessed 14 May 2020

  15. Rusu, R., Cousins, S.: 3D is here: point cloud library (PCL). In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 1–4, May 2011. https://doi.org/10.1109/ICRA.2011.5980567

  16. Velas, M., Spanel, M., Materna, Z., Herout, A.: Calibration of RGB camera with velodyne lidar. In: Communication Papers Proceedings International Conference on Computer Graphics, Visualization and Computer Vision (WSCG) (2014)

    Google Scholar 

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Authors and Affiliations

  1. Institute of Control and Computation Engineering, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665, Warsaw, Poland

    Artur Wilkowski

  2. United Robots Sp. z o.o., ul. Świeradowska 47, 02-662, Warsaw, Poland

    Dariusz Mańkowski

Authors
  1. Artur Wilkowski
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  2. Dariusz Mańkowski
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Correspondence to Artur Wilkowski .

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Editors and Affiliations

  1. Institute of Information Technology, Warsaw University of Life Sciences - SGGW, Warsaw, Poland

    Leszek J. Chmielewski

  2. Institute of Information Technology, Warsaw University of Life Sciences - SGGW, Warsaw, Poland

    Ryszard Kozera

  3. Institute of Information Technology, Warsaw University of Life Sciences - SGGW, Warsaw, Poland

    Arkadiusz Orłowski

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Wilkowski, A., Mańkowski, D. (2020). RGB-D and Lidar Calibration Supported by GPU. In: Chmielewski, L.J., Kozera, R., Orłowski, A. (eds) Computer Vision and Graphics. ICCVG 2020. Lecture Notes in Computer Science(), vol 12334. Springer, Cham. https://doi.org/10.1007/978-3-030-59006-2_19

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  • DOI: https://doi.org/10.1007/978-3-030-59006-2_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59005-5

  • Online ISBN: 978-3-030-59006-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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