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CS Freiburg: Global View by Cooperative Sensing

  • Markus Dietl
  • Jens-Steffen Gutmann
  • Bernhard Nebel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2377)

Abstract

Global vision systems as found in the small size league are prohibited in the middle size league. This paper presents methods for creating a global view of the world by cooperative sensing of a team of robots. We develop a multi-object tracking algorithm based on Kalman filtering and a single-object tracking method involving a combination of Kalman filtering and Markov localization for outlier detection. We apply these methods for robots participating in the middle-size league and compare them to a simple averaging method. Results including situations from real competition games are presented.

Keywords

Mobile Robot Data Association Sensor Fusion Ball Position World Model 
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 2002

Authors and Affiliations

  • Markus Dietl
    • 1
  • Jens-Steffen Gutmann
    • 1
  • Bernhard Nebel
    • 1
  1. 1.Institut für InformatikUniversität FreiburgFreiburgGermany

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