A gait pattern planning algorithm based on linear coupled oscillator model for humanoid robots

For the gait pattern planning algorithm of humanoid robots with the linear coupled oscillator model, some oscillator parameters were chosen by manual adjustment, which makes it difficult to get the parameters values that could ensure stable walking. To reduce the time of parameter selection and simplify the gait planning algorithm, a parameter selection algorithm based on linear coupled model for humanoid robots was proposed. By combining the walking speed, oscillation amplitude of the mass center during walking, and the trajectory curvature of ZMP, the optimization goal was established. The stable margin was defined and chosen as a constraint condition, and the nonlinear constraint method was used to obtain the optimization parameters which could ensure stable walking at faster speed. Simulation experiment demonstrated that the optimization parameters could ensure stable walking with rich stable margin. The proposed method was implemented on the open humanoid platform DARwIn-OP, and the results indicate that the optimized parameters in the linear coupled oscillator can achieve stable walking with fast gait pattern generation.