Statistical Modeling and Calibration of Triangulation Lidars

Anas Alhashimi, Damiano Varagnolo, Thomas Gustafsson

Abstract

We aim at developing statistical tools that improve the accuracy and precision of the measurements returned by triangulation Light Detection and Rangings (Lidars). To this aim we: i) propose and validate a novel model that describes the statistics of the measurements of these Lidars, and that is built starting from mechanical considerations on the geometry and properties of their pinhole lens - CCD camera systems; ii) build, starting from this novel statistical model, a Maximum Likelihood (ML) / Akaike Information Criterion (AIC) - based sensor calibration algorithm that exploits training information collected in a controlled environment; iii) develop ML and Least Squares (LS) strategies that use the calibration results to statistically process the raw sensor measurements in non controlled environments. The overall technique allowed us to obtain empirical improvements of the normalized Mean Squared Error (MSE) from 0.0789 to 0.0046.

References

  1. Alhashimi, A., Varagnolo, D., and Gustafsson, T. (2015). Joint temperature-lasing mode compensation for timeof-flight lidar sensors. Sensors, 15(12):31205-31223.
  2. Anderson, D., Herman, H., and Kelly, A. (2005). Experimental characterization of commercial flash ladar devices. In International Conference of Sensing and Technology, volume 2.
  3. Andreasson, H., Triebel, R., and Burgard, W. (2005). Improving plane extraction from 3d data by fusing laser data and vision. In Intelligent Robots and Systems, 2005.(IROS 2005). 2005 IEEE/RSJ International Conference on, pages 2656-2661. IEEE.
  4. Atanacio-Jiménez, G., González-Barbosa, J.-J., HurtadoRamos, J. B., Ornelas-Rodríguez, F. J., JiménezHernández, H., García-Ramirez, T., and GonzálezBarbosa, R. (2011). Lidar velodyne hdl-64e calibration using pattern planes. International Journal of Advanced Robotic Systems, 8(5):70-82.
  5. Blais, F. (2004). Review of 20 years of range sensor development. Journal of Electronic Imaging, 13(1).
  6. Brown, D. C. (1964). An advanced reduction and calibration for photogrammetric cameras. Technical report, DTIC Document.
  7. Campos, D., Santos, J., Gonçalves, J., and Costa, P. (2016). Modeling and simulation of a hacked neato xv-11 laser scanner. In Robot 2015: Second Iberian Robotics Conference, pages 425-436. Springer.
  8. Chen, C.-Y. and Chien, H.-J. (2012). On-site sensor recalibration of a spinning multi-beam lidar system using automatically-detected planar targets. Sensors, 12(10):13736-13752.
  9. Croarkin, C. and Tobias, P. (2006). e-handbook of statistical NIST/SEMATECH, July. Available http://www.itl.nist.gov/div898/handbook.
  10. Duane, C. B. (1971). Close-range camera calibration. Photogrammetric engineering, 37(8):855-866.
  11. Glennie, C. (2012). Calibration and kinematic analysis of the velodyne hdl-64e s2 lidar sensor. Photogrammetric Engineering & Remote Sensing, 78(4):339-347.
  12. Glennie, C. and Lichti, D. D. (2010). Static calibration and analysis of the velodyne hdl-64e s2 for high accuracy mobile scanning. Remote Sensing, 2(6):1610-1624.
  13. Glennie, C. and Lichti, D. D. (2011). Temporal stability of the velodyne hdl-64e s2 scanner for high accuracy scanning applications. Remote Sensing, 3(3):539- 553.
  14. Gong, X., Lin, Y., and Liu, J. (2013). 3D LIDAR-camera extrinsic calibration using an arbitrary trihedron. Sensors, 13(2):1902-1918.
  15. Gordon, M. and Meidow, J. (2013). Calibration of a multibeam laser system by using a tls-generated reference. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-5 W, 2:85-90.
  16. Gustafsson, F. (2010). Statistical sensor fusion. Studentlitteratur,.
  17. Jokinen, O. (1999). Self-calibration of a light striping system by matching multiple 3-d profile maps. In 3- D Digital Imaging and Modeling, 1999. Proceedings. Second International Conference on, pages 180-190. IEEE.
  18. Kneip, L., Tâche, F., Caprari, G., and Siegwart, R. (2009). Characterization of the compact hokuyo urg-04lx 2d laser range scanner. In Robotics and Automation, 2009. ICRA'09. IEEE International Conference on, pages 1447-1454. IEEE.
  19. Konolige, K., Augenbraun, J., Donaldson, N., Fiebig, C., and Shah, P. (2008). A low-cost laser distance sensor. In Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on, pages 3002-3008. IEEE.
  20. Kümmerle, R., Grisetti, G., and Burgard, W. (2011). Simultaneous calibration, localization, and mapping. In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages 3716- 3721. IEEE.
  21. Lee, K.-H. and Ehsani, R. (2008). Comparison of two 2d laser scanners for sensing object distances, shapes, and surface patterns. Computers and electronics in agriculture, 60(2):250-262.
  22. Lima, J., Gonçalves, J., and Costa, P. J. (2015). Modeling of a low cost laser scanner sensor. In CONTROLO'2014- Proceedings of the 11th Portuguese Conference on Automatic Control, pages 697-705. Springer.
  23. McIvor, A. M. (1999). Calibration of a laser stripe profiler. In 3-D Digital Imaging and Modeling, 1999. Proceedings. Second International Conference on, pages 92- 98. IEEE.
  24. Mei, C. and Rives, P. (2006). Calibration between a central catadioptric camera and a laser range finder for robotic applications. In Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on, pages 532-537. IEEE.
  25. Mirzaei, F. M., Kottas, D. G., and Roumeliotis, S. I. (2012). 3d lidar-camera intrinsic and extrinsic calibration: Identifiability and analytical least-squares-based initialization. The International Journal of Robotics Research, 31(4):452-467.
  26. Muhammad, N. and Lacroix, S. (2010). Calibration of a rotating multi-beam lidar. In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pages 5648-5653. IEEE.
  27. Park, Y., Yun, S., Won, C. S., Cho, K., Um, K., and Sim, S. (2014). Calibration between color camera and 3d lidar instruments with a polygonal planar board. Sensors, 14(3):5333-5353.
  28. Reina, A. and Gonzales, J. (1997). Characterization of a radial laser scanner for mobile robot navigation. In Intelligent Robots and Systems, 1997. IROS'97., Proceedings of the 1997 IEEE/RSJ International Conference on, volume 2, pages 579-585. IEEE.
  29. Sanz-Cortiella, R., Llorens-Calveras, J., Rosell-Polo, J. R., Gregorio-Lopez, E., and Palacin-Roca, J. (2011). Characterisation of the lms200 laser beam under the influence of blockage surfaces. influence on 3d scanning of tree orchards. Sensors, 11(3):2751-2772.
  30. Tang, P., Akinci, B., and Huber, D. (2009). Quantification of edge loss of laser scanned data at spatial discontinuities. Automation in Construction, 18(8):1070-1083.
  31. Teichman, A., Miller, S., and Thrun, S. (2013). Unsupervised intrinsic calibration of depth sensors via slam. In Robotics: Science and Systems. Citeseer.
  32. Tiddeman, B., Duffy, N., Rabey, G., and Lokier, J. (1998). Laser-video scanner calibration without the use of a frame store. In Vision, Image and Signal Processing, IEE Proceedings-, volume 145, pages 244-248. IET.
  33. Tuley, J., Vandapel, N., and Hebert, M. (2005). Analysis and removal of artifacts in 3-d ladar data. In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pages 2203- 2210. IEEE.
  34. Wei, G.-Q. and Hirzinger, G. (1998). Active self-calibration of hand-mounted laser range finders. Robotics and Automation, IEEE Transactions on, 14(3):493-497.
  35. Weng, J., Cohen, P., and Herniou, M. (1992). Camera calibration with distortion models and accuracy evaluation. IEEE Transactions on Pattern Analysis & Machine Intelligence, 14(10):965-980.
  36. Ye, C. and Borenstein, J. (2002). Characterization of a 2-d laser scanner for mobile robot obstacle negotiation. In ICRA, pages 2512-2518.
  37. Zhang, Q. and Pless, R. (2004a). Constraints for heterogeneous sensor auto-calibration. In Computer Vision and Pattern Recognition Workshop, 2004. CVPRW'04. Conference on, pages 38-38. IEEE.
  38. Zhang, Q. and Pless, R. (2004b). Extrinsic calibration of a camera and laser range finder (improves camera calibration). In Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on, volume 3, pages 2301- 2306. IEEE.
  39. Zhang, Z. (2000). A flexible new technique for camera calibration. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 22(11):1330-1334.
Download


Paper Citation


in Harvard Style

Alhashimi A., Varagnolo D. and Gustafsson T. (2016). Statistical Modeling and Calibration of Triangulation Lidars . In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-198-4, pages 308-317. DOI: 10.5220/0005965803080317


in Bibtex Style

@conference{icinco16,
author={Anas Alhashimi and Damiano Varagnolo and Thomas Gustafsson},
title={Statistical Modeling and Calibration of Triangulation Lidars},
booktitle={Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2016},
pages={308-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005965803080317},
isbn={978-989-758-198-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Statistical Modeling and Calibration of Triangulation Lidars
SN - 978-989-758-198-4
AU - Alhashimi A.
AU - Varagnolo D.
AU - Gustafsson T.
PY - 2016
SP - 308
EP - 317
DO - 10.5220/0005965803080317