A Gait Optimization Smoothing Penalty Function Method for Bipedal Robot via DMOC

摘要

For periodic gait optimization problem of bipedal walking robot, based on discrete mechanics and optimal control (DMOC), a class of smoothing penalty function method is proposed. The optimal control strategy and trajectory are solved by a new smoothing exact penalty function algorithm. The algorithm can quickly converge to a stable gait cycle independent the selection of the initial gait, otherwise, the algorithm only needs one step correction and then generate a stable gait cycle. Numerical simulation results show that the algorithm is feasible and effective. The algorithm makes the bipedal robot walk efficiently and stably on the even terrain.