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Real-Time Active Vision by Entropy Minimization Applied to Localization

  • Stefan Czarnetzki
  • Sören Kerner
  • Michael Kruse
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6556)

Abstract

This paper presents an active vision approach to enhance mobile robot localization. A particle filter localization is extended with a module to find active vision decisions that are optimal based on the current localization and its uncertainty. Optimality is expressed as a criterion of entropy minimization. Further approximations are introduced to enable real-time computation. Both the usefulness of the presented approach in a RoboCup scenario and the performance and quality of the approximations are evaluated in different static and dynamic situations.

Keywords

Humanoid Robot Belief State Active Vision Sonar Sensor Side Line 
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 2011

Authors and Affiliations

  • Stefan Czarnetzki
    • 1
  • Sören Kerner
    • 1
  • Michael Kruse
    • 1
  1. 1.Robotics Research Institute, Section Information TechnologyTU Dortmund UniversityDortmundGermany

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