Abstract
Controlling a biped robot with several degrees of freedom is a challenging task that takes the attention of several researchers in the fields of biology, physics, electronics, computer science and mechanics. For a humanoid robot to perform in complex environments, fast, stable and adaptive behaviors are required. This paper proposes a solution for automatic generation of a walking gait using genetic algorithms (GA). A method based on partial Fourier series was developed for joint trajectory planning. GAs were then used for offline generation of the parameters that define the gait. GAs proved to be a powerful method for automatic generation of humanoid behaviors resulting on a walk forward velocity of 0.51m/s which is a good result considering the results of the three best teams of RoboCup 3D simulation league for the same movement.
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Picado, H., Gestal, M., Lau, N., Reis, L.P., Tomé, A.M. (2009). Automatic Generation of Biped Walk Behavior Using Genetic Algorithms. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_101
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DOI: https://doi.org/10.1007/978-3-642-02478-8_101
Publisher Name: Springer, Berlin, Heidelberg
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