Parameter Optimization of a Signal-Based Omni-Directional Biped Locomotion Using Evolutionary Strategies

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The ultimate goal of RoboCup depends heavily on the advances in the development of humanoid robots. Flexible walking is a crucial part of playing soccer and bipedal walking has been a very active research topic in RoboCup. In this paper a signal-based omnidirectional walking algorithm for the Aldebaran Nao humanoid robot is presented. Inspired from the existing methods in the literature, the proposed method models the omni-directional motion as the combination of a set of periodic signals. The parameters controlling the characteristics of the signals are encoded into genes and Evolutionary Strategies is used to learn an optimal set of parameters.