Parameter Optimization of a Signal-Based Omni-Directional Biped Locomotion Using Evolutionary Strategies
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.
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- 3.Pinto, C., Golubitsky, M.: Central pattern generators for bipedal locomotion. J. Math. Biol. (2006)Google Scholar
- 4.Behnke, S.: Online trajectory generation for omnidirectional biped walking. In: ICRA, pp. 1597–1603 (2006)Google Scholar
- 5.Faber, F., Behnke, S.: Stochastic optimization of bipedal walking using gyro feedback and phase resetting. In: Proceedings of the International Conference on Humanoid Robots (Humanoids) (2007)Google Scholar
- 6.Aldebaran Robotics, http://www.aldebaran-robotics.com/eng/
- 8.Shafii, N., Seyed Javadi, M.H., Kimiaghalam, B.: A truncated fourier series with genetic algorithm for the control of biped locomotion. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics (2009)Google Scholar
- 10.Cyberbotics (2010), http://www.cyberbotics.com/