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Robust Multi-robot Object Localization Using Fuzzy Logic

  • Juan Pedro Cánovas
  • Kevin LeBlanc
  • Alessandro Saffiotti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)

Abstract

Cooperative localization of objects is an important challenge in multi-robot systems. We propose a new approach to this problem where we see each robot as an expert which shares unreliable information about object locations. The information provided by different robots is then combined using fuzzy logic techniques, in order to reach a consensus between the robots. This contrasts with most current probabilistic techniques, which average information from different robots in order to obtain a tradeoff, and can thus incur well-known problems when information is unreliable. In addition, our approach does not assume that the robots have accurate self-localization. Instead, uncertainty in the pose of the sensing robot is propagated to object position estimates. We present experimental results obtained on a team of Sony AIBO robots, where we share information about the location of the ball in the RoboCup domain.

Keywords

Fuzzy Logic Object Localization Ball Position Position Grid Cooperative Localization 
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 2005

Authors and Affiliations

  • Juan Pedro Cánovas
    • 1
  • Kevin LeBlanc
    • 2
  • Alessandro Saffiotti
    • 2
  1. 1.Dept. of Information and Comm. Eng.University of MurciaMurciaSpain
  2. 2.AASS Mobile Robotics Lab, Dpt. TechnologyÖrebro UniversityÖrebroSweden

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