Automatic Generation of Biped Walk Behavior Using Genetic Algorithms

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.

• Type: Conference
• Year: 2009
• Where: IWANN
• Authors: Hugo Picado, Marcos Gestal, Nuno Lau, Luís Paulo Reis, Ana Maria Tomé
• Keywords: Artificial Intelligence, Automatic Generation, Humanoid Robot, IWANN 2009, Partial Fourier Series