An optimized gait generator based on fourier series towards fast and robust biped locomotion involving arms swing

Bipedal locomotion is one of the most challenging problems in control, artificial intelligence, mechanics and other related fields. In this article a model free approach with emphasis on making robot´s walking more stable and faster is presented. In this regard we use particle swarm optimization (PSO) to optimize the signals produced by truncated Fourier series (TFS) which control joints´ angels. The role of hands is also considered to smooth walking and to increase its robustness. For the first time a new method will be introduced to improve the speed and robustness of bipedal walking by refining signals and reducing the role of inertia. Simulation results show this approach can make the robot´s walking more stable and faster than walking without considering the role of hands and inertia effect.