Automatic Generation of Biped Walk Behavior Using Genetic Algorithms
Identifieur interne : 002059 ( Istex/Curation ); précédent : 002058; suivant : 002060Automatic Generation of Biped Walk Behavior Using Genetic Algorithms
Auteurs : Hugo Picado [Portugal] ; Marcos Gestal [Espagne] ; Nuno Lau [Portugal] ; Luis P. Reis [Portugal] ; Ana M. Tomé [Portugal]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2009.
Abstract
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.
Url:
DOI: 10.1007/978-3-642-02478-8_101
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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.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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