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Autores:
Hugo Picado, Marcos Gestal, Nuno Lau, Ana Mariá Tomé, Luis P. Reis
Título: Automatic Generation of Biped Walk Behaviour Using Genetic Algorithms
Congreso: International Work-Conference on Artificial Neural Networks (IWANN2009)
Lugar Celebración: Salamanca (España)
Fecha Celebración: 10-12 de Junio de 2009
Publicación: Proceedings of IWANN2009
ISBN: 3-642-02447-7
Páginas: 805-812
Editorial: Springer Verlag
Fecha Publicación: Junio 2009
doi: 10.1007/978-3-642-02478-8_101
Congreso indexado en Australian Ranking of ICT Conference (CORE): categoria B
Congreso indexado en CiteSeer: 975/1221
Congreso indexado en Computer Science Conference Ranking: 0.55 (55/701)

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.