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Adaptive Methods to Improve Self-localization in Robot Soccer

  • Ingo Dahm
  • Jens Ziegler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2752)

Abstract

This paper shows adaptive strategies to improve the reliability and performance of self-localization in robot soccer with legged robots. Adaptiveness is the common feature of the presented algorithms and has proved essential to enhance the quality of localization by a new classification technique, essential to increase the confidence level of internal information about the environment by extracting reliability information and by communicating them via parameterizable acoustic communication, and essential to circumvent manual implementations of walking patterns by evolving them automatically.

Keywords

Genetic Program Code Rate Adaptive Method Parity Check Convolutional Code 
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 2003

Authors and Affiliations

  • Ingo Dahm
    • 1
  • Jens Ziegler
    • 2
  1. 1.Computer Engineering InstituteUniversity of DortmundDortmundGermany
  2. 2.Dept. of Computer ScienceUniversity of DortmundDortmundGermany

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