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Evolutionary Gait-Optimization Using a Fitness Function Based on Proprioception

  • Thomas Röfer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)

Abstract

This paper presents a new approach to optimize gait parameter sets using evolutionary algorithms. It separates the crossover-step of the evolutionary algorithm into an interpolating step and an extrapolating step, which allows for solving optimization problems with a small population, which is an essential for robotics applications. In contrast to other approaches, odometry is used to assess the quality of a gait. Thereby, omni-directional gaits can be evolved. Some experiments with the Sony Aibo models ERS-210 and ERS-7 prove the performance of the approach including the fastest gait found so far for the Aibo ERS-210.

Keywords

Fitness Function Gait Parameter Acceleration Sensor Ground Contact Quadruped Robot 
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

  • Thomas Röfer
    • 1
  1. 1.Center for Computing Technology (TZI), FB 3Universität Bremen 

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