ZMP-Based Online Jumping Pattern Generation for a One-Legged Robot

This paper is aimed at presenting a method to generate online jumping patterns, which can be applied to one-legged jumping robots and optionally to humanoid robots. Our proposed method is based on ensuring the overall dynamic balance through the complete jumping cycle. To be able to reach this goal, we discretized the zero moment point equation in polar coordinates so that we are able to include angular momentum information in a natural way. Thus, undesired torso angle fluctuation is expected to be more restrainable compared to other methods in which angular momentum information is ignored or zero referenced. Moreover, we unified support and flight phases in terms of motion generation. Having obtained successful simulation results and vertical jumping experiments in our previous work, we conducted forward jumping experiments. As the result, we obtained successful and repetitive jumping cycles, which satisfactorily verify the proposed method.