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KI - Künstliche Intelligenz

, Volume 28, Issue 1, pp 53–57 | Cite as

Automatic Generation of 3D Polygon Maps for Mobile Robots

  • Thomas Wiemann
Doctoral and Postdoctoral Dissertations
  • 192 Downloads

Abstract

The recent advance in 3D measurement technology, especially 3D laser scanners and RGB-D sensors like Microsoft Kinect, has made 3D point clouds feasibly accessible on mobile robots. Together with efficient SLAM algorithms, it is now possible to generate 3D point clouds of large environments like whole buildings or even cities at high speed and low cost. The problem is that these point clouds are usually not a suitable representation for classic robotic tasks like localization or even more sophisticated problems like scene interpretation. This thesis presents methods to create polygonal environment representations that can be used for semantic mapping and object recognition.

Keywords

Point Cloud Mobile Robot Terrestrial Laser Scanner Point Cloud Data Mesh Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Amenta N, Choi S, Kolluri RK (2001) The power crust. In: Proc. ACM symposium on solid modeling and applicationsGoogle Scholar
  2. 2.
    Girardeau-Montaut D, Rouxa M, Marc R, Thibault G (2005) Change detection on point cloud data acquired with a ground laser scanner. In: ISPRS workshop laser scanningGoogle Scholar
  3. 3.
    Günther M, Wiemann T, Albrecht S, Hertzberg J (2011) Model-based object recognition from 3d laser data. In: Proc. KI 2011, Springer-VerlagGoogle Scholar
  4. 4.
    Hoppe H, DeRose T, Duchamp T, McDonald J, Stuetzle W (1992) Surface reconstruction from unorganized points. Computer Graphics 26(2)Google Scholar
  5. 5.
    Izadi S, Newcombe RA, Kim D, Hilliges O, Molyneaux D, Hodges S, Kohli P, Shotton J, Davison AJ, Fitzgibbon A (2011) Kinectfusion: real-time dynamic 3d surface reconstruction and interaction. In: ACM SIGGRAPH 2011 TalksGoogle Scholar
  6. 6.
    Kazhdan M, Bolitho M, Hoppe H (2006) Poisson surface reconstruction. In: Proc. SGP ’06Google Scholar
  7. 7.
    Kobbelt LP, Botsch M, Schwanecke U, Seidel HP (2001) Feature sensitive surface extraction from volume data. In: Proc. ACM SIGGRAPH ’01Google Scholar
  8. 8.
    Lorensen WE, Cline HE (1987) Marching cubes: a high resolution 3D surface construction algorithm. In: ACM SIGGRAPHGoogle Scholar
  9. 9.
    Wiemann T (2013) Automatische Generierung dreidimensionaler Polygonkarten für mobile Roboter. PhD thesis, Universität Osnabrück, urn:nbn:de:gbv:700-2013050710827Google Scholar
  10. 10.
    Wiemann T, Lingemann K, Nüchter A, Hertzberg J (2012) A toolkit for automatic generation of polygonal maps —las vegas reconstruction. In: Proc. ROBOTIK 2012, http://www.las-vegas.uni-osnabrueck.de
  11. 11.
    Wiemann T, Lingemann K, Hertzberg J (2013) Automatic map creation for environment modelling in robotic simulators. In: Proc. ECMS 2013Google Scholar
  12. 12.
    Wülfing J, Hertzberg J, Lingemann K, Nüchter A, Stiene S, Wiemann T (2010) Towards real time robot 6d localization in a polygonal indoor map based on 3d tof camera data. In: Proc. IAV 2010Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Universität OsnabrückOsnabrückGermany

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