Footstep Planning for Biped Robot based on Fuzzy Q-Learning Approach

The biped robots have more flexible mechanical systems and they can move in more complex environment than wheeled robots. Their abilities to step over both static and dynamic obstacles allow to the biped robots to cross an uneven terrain where ordinary wheeled robots can fail. In this paper we present a footstep planning for biped robots allowing them to step over dynamic obstacles. Our footstep planning strategy is based on a fuzzy Q-learning concept. In comparison with other previous works, one of the most appealing interest of our approach is its good robustness because the proposed footstep planning is operational for both constant and random velocity of the obstacle.

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