Abstract
Stable walking is the most basic human behavior of humanoid robots and one of the most important research contents in the field of robots. However, reasonable gait planning is the basis for the stable walking of humanoid robots. Therefore, in this paper, we analyzes one of the CPG model and applies it to our own laboratory robot, aim at the problem that it is prone to shock forward and backward in the Robot Athletics Sprint, this paper increased centroid offset control and proposed an algorithm to optimize the walking control parameters for the improvement of the whole gait planning algorithm. Stability margin of ZMP and balanced oscillator amplitude were combined as an optimization target, genetic algorithm was used as a solution tool, the purpose is to get the optimal gait parameters under different input speed. The proposed algorithm was tested on the laboratory robot, the results of simulation and real robot experiments show the effectiveness of our algorithm.
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