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Fast method of 3D map building based on laser range data

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EN
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EN
In this paper, we consider the problem of 3D maps building based on the 3D laser scanner indications. The map of the environmem is represented as a 2D array of cells. Each cell represents rectangular region of the scene and consits of list of objects. The key idea of the system is lines extraction from the raw laser data and assigning them to the proper cells. Based on the lines, a set of objects (planes) is built and assigned to each cell. Objects represent obstacles in the environment. The main advantages of the system are real-time map building and Iow memory consumption. We prove that the system works property in real indoor environment but the system can be extended in order ta buiit the map of uristructured robots surrounding.
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autor
  • Institute of Fundamental Technological Research , Polish Academy of Sciences, ul. Świetokrzyska 21, 00-049 Warsaw, Poland, bsiem@ippt.gov.pl
Bibliografia
  • [1] Aldon M. and J. Borges G.A., "Robustified estimation algorihthms for mobile robot localization based on geometrical. environment maps", Robotics and Autonomous Systems, 2003, no. 45, pp. 131-159.
  • [2] O. Chum and J. Matas, "Randomized Ransac with T (d,d) test", British Machine Vision Cor.ference. University of Cardiff, 2002, pages 448-457.
  • [3] J. T. Feddema and C. Q. Little, "Rapid world modeling: Fitting range data to geometric primitives", in: Proceedings of IEEE ICRA , 1997, pp. 2807-2812.
  • [4] S. Florczyk, Robot vision, Wiley-VCH Verlag, 2005.
  • [5] F. Lu and E.E. Milios, “Appearance based processes for visual navigation", in: Proceedings of Symposium on Intelligent Robotics Systems, 1999, pages 227-236.
  • [6] Betke M. and Gurvits L., "Mobile robot Localization using Landmarks", IEEE Transactions on Robotics and Automation, vol. 13, April 1997, no. 2 pages 135-142.
  • [7] K. Niewiarowski, "3D map building and visualization by mobile robots" (in polish) - master thesis, Warsaw University of Technology, 2006.
  • [8] Andersen C.S., Jones S., and Crowley J.L., "Appearance based processes for visual navigation", in: Proceedings of Symposium on Intelligent Robotics Systems, 1999, pages 227-236.
  • [9] Thrun S., Fox D., and Burgard W., "Probabilistic approach to concurrent mapping and localization for mobile robots", Machine Learning, 1997, no. 31, pp. 29-53.
  • [10] Thrun S., Fox D., and Burgard W., "Probabilistic mapping of an environment by a mobile robot", in: Proceedings of IEEE ICRA, 1998, pages 1546-1551.
  • [11] G. Sakas and J. Hartig. "Interactive visualization of large scalar voxel fields", in: Proceedings IEEE visualization'92, Boston-MA, USA, 19-2 2 October 1992, pp. 29-36.
  • [12] R. Sawwa, B. Siemiątkowska, and J. Racz,”2.5D map building based on lrf readouts", in: 3rd Int. Symp. on Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 1997, pages 13-115.
  • [13] R. Sawwa, B. Siemiątkowska, and J. Racz, "A laser range finder for mobile robot navigation" in: 28-th International Symposium on Robotics, Detroit USA. 1997, pages 13-15.
  • [14] W. Schroeder, J. Zarge, and W. Lorensen, „Decimation of triangle meshes", Computer Graphics (SIGGRAPH'92 Proceedings), vol. 26, no. 2,July 1992, pp. 65-70.
  • [15] S. Thrun, W. Burgard, and D. Fox, Probabilistic robotics, MIT-Press,2005.
  • [16] R. Triebel, B. Frank, J. Meyer, and W. Burgard, "First steps towards a robotic system for flexible volumetric mapping of indoor environments", CD-ROM, IAV04, 2004.
  • [17] J. Weingarten and R. Siegwart, “EKF -based 3D SLAM for structured environment construction", in: Proceedings of IROS 2005.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUJ5-0012-0011
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