Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02478-8_101 | IWANN (1) |
Keywords | Field | DocType |
genetic algorithms,adaptive behavior,powerful method,challenging task,automatic generation,humanoid behavior,offline generation,best team,walking gait,biped robot,humanoid robot,genetic algorithm | Computer vision,Gait,Computer science,Simulation,3d simulation,Fourier series,Artificial intelligence,Robot,Adaptive behavior,Genetic algorithm,Robotics,Humanoid robot | Conference |
Volume | ISSN | Citations |
5517 | 0302-9743 | 12 |
PageRank | References | Authors |
0.93 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hugo Picado | 1 | 12 | 0.93 |
| Marcos Gestal | 2 | 43 | 8.46 |
| Nuno Lau | 3 | 81 | 12.70 |
| Luis P. Reis | 4 | 15 | 4.07 |
| Ana M. Tomé | 5 | 12 | 1.27 |