International Journal of Robotics Research
Biped Locomotion
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Automatic Generation of Biped Walk Behavior Using Genetic Algorithms
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Biped walking by using all joint movements and DOFs in both directions (sagittal plane and coronal plane) is one of the most complicated research topics in robotics. In this paper, angular trajectories of a stable biped walking for a humanoid robot are generated by a Truncated Fourier Series (TFS) approach. The movements of legs and arms in sagittal plane are implemented by an optimized gait generator and a new model is proposed that can also produce the movement of legs in coronal plane based on TFS. Particle Swarm Optimization (PSO) is used to find the best angular trajectories and optimize TFS. Experimental results show that the using joints movements in sagittal and coronal planes to compose the walking skill allowed the biped robot to walk faster than previous methods that only used the joints in sagittal plane.