Towards Geometric Mapping for Semi-autonomous Mobile Robots

  • Georg Arbeiter
  • Richard Bormann
  • Jan Fischer
  • Martin Hägele
  • Alexander Verl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7463)


Semi-autonomous mobile robots are a promising alternative for tasks that are too challenging for autonomous robots. Especially in an unstructured environment, full autonomy is still far from being realized. In order to enable the human operator to control the robot properly, visualization of the environment is crucial. In this paper, we introduce a pipeline for geometric mapping that uses narrow field of view RGB-D cameras as input source and builds a geometric map of the environment while the robot either is operated manually or moves autonomously. Geometric shapes are extracted from subsequent sensor frames and are clipped and merged in a geometric feature map. Evaluation is done both in simulation and on the real robot.


Point Cloud Iterative Close Point Iterative Close Point Kinect Camera Common Coordinate System 
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 2012

Authors and Affiliations

  • Georg Arbeiter
    • 1
  • Richard Bormann
    • 1
  • Jan Fischer
    • 1
  • Martin Hägele
    • 1
  • Alexander Verl
    • 1
  1. 1.Institute for Manufacturing Engineering and AutomationFraunhofer IPAStuttgartGermany

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