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3D Mapping with Semantic Knowledge

  • Andreas Nüchter
  • Oliver Wulf
  • Kai Lingemann
  • Joachim Hertzberg
  • Bernardo Wagner
  • Hartmut Surmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4020)

Abstract

A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360°. The matching is based on semantic information. Surface attributes are extracted and incorporated in a forest of search trees in order to associate the data, i.e., to establish correspondences. The new approach results in advances in speed and reliability.

Keywords

Mobile Robot Iterative Close Point Semantic Knowledge Point Pair Point Correspondence 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Andreas Nüchter
    • 1
  • Oliver Wulf
    • 2
  • Kai Lingemann
    • 1
  • Joachim Hertzberg
    • 1
  • Bernardo Wagner
    • 2
  • Hartmut Surmann
    • 3
  1. 1.Institute for Computer Science, Knowledge-Based Systems Research GroupUniversity of OsnabrückOsnabrückGermany
  2. 2.Institute for Systems Engineering (ISE/RTS)University of HannoverHannoverGermany
  3. 3.Fraunhofer Institute for Autonomous Intelligent Systems (AIS)Sankt AugustinGermany

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