Simultaneous Localization and Mapping in Buildings

  • Martin Werner


Simultaneous localization and mapping (SLAM) is a family of algorithms to generate map information while positioning the moving target at the same time. SLAM algorithms rely on many elementary algorithms such as feature point tracking, loop detection, random sample consensus, surface simplification, and more. This chapter aims to bring together a closed exposition of these algorithms and their application inside buildings.


Point Cloud Optical Flow Scale Invariant Feature Transform Iterative Close Point Iterative Close Point Algorithm 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Martin Werner
    • 1
  1. 1.Ludwig-Maximilians-Universität MünchenMunichGermany

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