PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Benchmark of 6D SLAM (6d simultaneous localization and mapping) algorithms with robotic mobile mapping systems

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This work concerns the study of 6DSLAM algorithms with an application of robotic mobile mapping systems. The architecture of the 6DSLAM algorithm is designed for evaluation of different data registration strategies. The algorithm is composed of the iterative registration component, thus ICP (Iterative Closest Point), ICP (point to projection), ICP with semantic discrimination of points, LS3D (Least Square Surface Matching), NDT (Normal Distribution Transform) can be chosen. Loop closing is based on LUM and LS3D. The main research goal was to investigate the semantic discrimination of measured points that improve the accuracy of final map especially in demanding scenarios such as multi-level maps (e.g., climbing stairs). The parallel programming based nearest neighborhood search implementation such as point to point, point to projection, semantic discrimination of points is used. The 6DSLAM framework is based on modified 3DTK and PCL open source libraries and parallel programming techniques using NVIDIA CUDA. The paper shows experiments that are demonstrating advantages of proposed approach in relation to practical applications. The major added value of presented research is the qualitative and quantitative evaluation based on realistic scenarios including ground truth data obtained by geodetic survey. The research novelty looking from mobile robotics is the evaluation of LS3D algorithm well known in geodesy.
Rocznik
Strony
276--295
Opis fizyczny
Bibliogr. 27 poz., fig., tab.
Twórcy
  • Institute of Fundamental Technological Research, Polish Academy of Science, Warsaw, Poland IPPT PAN
autor
  • Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie, Kognitive Mobile Systeme, Wachtberg, Germany FKIE
autor
  • Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie, Kognitive Mobile Systeme, Wachtberg, Germany FKIE
autor
  • Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie, Kognitive Mobile Systeme, Wachtberg, Germany FKIE
  • Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie, Kognitive Mobile Systeme, Wachtberg, Germany FKIE
Bibliografia
  • 1. 3DTK - The 3D Toolkit, http://slam6d.sourceforge.net.
  • 2. Akca D., Least Squares 3D surface matching. Ph.D. thesis, Institute of Geodesy and Photogrammetry, ETH Zurich, Switzerland, ISBN 3-906467-63-5, Mitteilungen Nr. 92, 78 pages, 2007.
  • 3. Akca D., Gruen A., Generalized Least Squares Multiple 3D Surface Matching, IAPRS Volume XXXVI, Part 3 / W52, 2007.
  • 4. Arun K.S., Huang T.S., Blostein S.D., Least-Squares Fitting of Two 3-D Point Sets, IEEE Trans. Pattern Anal. Mach. Intell., (9)5, pp. 698-700, 1987.
  • 5. Będkowski J., Maslowski A., de Cubber G., Real time 3D localization and mapping for USAR robotic application, Industrial Robot, (39)5, pp. 464-474, 2012.
  • 6. Będkowski J., Majek K., Nüchter A., General purpose computing on graphics processing units for robotic applications, Journal of Software Engineering for Robotics (JOSER) 4(1), pp. 23-33, 2013.
  • 7. Będkowski J., Majek K., Musialik P., Adamek A., Andrzejewski D., Czekaj D., Towards terrestrial 3D data registration improved by parallel programming and evaluated with geodetic precision, Automation in Construction Volume 47, pp. 78-91, 2014.
  • 8. Besl P.J., McKay N.D., A Method for Registration of 3-D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2), pp. 239-256, 1992.
  • 9. Biber P., Strafier W., The normal distributions transform: A new approach to laser scan matching. In Proc. IROS, volume 3, pp. 2743-2748, 2003.
  • 10. Borrmann D., Elseberg J., Lingemann K., Nüchter A., Hertzberg J., Globally Consistent 3D Mapping with Scan Matching. J. Robotics and Autonomous Sytems, 65(2), pp. 130-142, 2008.
  • 11. CUDA – Compute Unified Device Architecture, https://developer.nvidia.com/cuda-zone.
  • 12. Elseberg J., Borrmann D., Nüchter A., Efficient Processing of Large 3D Point Clouds, in: Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT11), Sarajevo, Bosnia, 2011.
  • 13. Elseberg J., Magnenat S., Siegwart R., Nüchter A., Comparison of nearest- neighbor-search strategies and implementations for efficient shape registration, Journal of Software Engineering for Robotics (JOSER) 3(1), pp. 2-12, 2012.
  • 14. Horn B.K.P., Closed-form solution of absolute orientation using unit quaternions, Journal of the Optical Society of America, 4(4), pp. 629-642, 1987.
  • 15. Horn B.K.P., Hilden H.M., Negahdaripour S., Closed-Form Solution of Absolute Orientation using Orthonormal Matrices, Journal of the Optical Society America, 5(7), pp. 1127-1135, 1988.
  • 16. Lorusso A., Eggert D.W., Fisher R.B., A Comparison of Four Algorithms for Estimating 3-D Rigid Transformations, 1995.
  • 17. Lu F., Milios E., Globally Consistent Range Scan Alignment for Environment Mapping. Autonomous Robots, 4, pp. 333-349, 1997.
  • 18. Magnusson M., Duckett T., A Comparison of 3D Registration Algorithms for Autonomous Underground Mining Vehicles, in: Proceedings of European Conference on Mobile Robots ECMR, pp. 86-91, 2005.
  • 19. Magnusson M., Lilienthal A., Duckett T., Scan registration for autonomous mining vehicles using 3D-NDT. Journal of Field Robotics, 24(10), pp. 803-827, 2007.
  • 20. Nüchter A., Surmann H., Lingemann K., Hertzberg J., Thrun S., 6D SLAM with an Application in Autonomous Mine Mapping, in: In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1998-2003, 2004.
  • 21. Nüchter A., Lingemann K., Hertzberg J., Surmann H., 6D SLAM - 3D mapping outdoor environments, Journal of Field Robotics 24(8-9), pp. 699-722, 2007.
  • 22. Nüchter A., Elseberg J., Schneider P., Paulus D., Study of parameterizations for the rigid body transformations of the scan registration problem, Comput. Vis. Image Underst., (114)8, pp. 963-980, 2010.
  • 23. PCL - Point Cloud Library, http://pointclouds.org.
  • 24. Qiu D., May S., Nüchter A., GPU-Accelerated Nearest Neighbor Search for 3D Registration, in: Proceedings of the 7th International Conference on Computer Vision Systems, ICVS09, Springer-Verlag, Berlin, Heidelberg, pp. 194-203, 2009.
  • 25. ROS - Robot Operating System, http://www.ros.org.
  • 26. Sprickerhof J., Nüchter A., Lingemann K., Hertzberg J., An Explicit Loop Closing Technique for 6D SLAM, in: I. Petrovic, A.J. Lilienthal (Eds.), Proceedings of the 4th European Conference on Mobile Robots, ECMR 09, September 23-25, 2009, Mlini/Dubrovnik, Croatia, KoREMA, pp. 229-234, 2009.
  • 27. Walker M.W., Shao L., Richard A. Volz, Estimating 3-D location parameters using dual number quaternions, CVGIP: Image Underst., (54)3, pp. 358-367, 1991.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-46b7c92d-8724-4cd8-a1ff-f1d69b004b88
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.