Automatic Generation of Biped Walk Behavior Using Genetic Algorithms

Authors:
Hugo Picado;Marcos Gestal;Nuno Lau;Luis P. Reis;Ana M. Tomé
Affiliations:
Institute of Electronics and Telematics Enginnering of Aveiro, Portugal and Dep. of Electronics, Telecommunications and Informatics, Univ. Aveiro, Portugal;Artificial Neural Network and Adaptive System Lab., Univ. Coruña, Spain;Institute of Electronics and Telematics Enginnering of Aveiro, Portugal and Dep. of Electronics, Telecommunications and Informatics, Univ. Aveiro, Portugal;Artificial Intelligence and Computer Science Lab., Univ. Porto, Portugal and Faculty of Engineering of the University of Porto, Portugal;Institute of Electronics and Telematics Enginnering of Aveiro, Portugal and Dep. of Electronics, Telecommunications and Informatics, Univ. Aveiro, Portugal
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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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.