Humanoid gait generation for walk-to locomotion using single-stage MPC

Ahmed Aboudonia, Nicola Scianca, D. Simone, L. Lanari, G. Oriolo
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引用次数: 9

Abstract

We consider the problem of gait generation for a humanoid robot that must walk to an assigned Cartesian goal. As a first solution, we consider a rather straightforward adaptation of our previous work: an external block produces high-level velocities, which are then tracked by a double-stage intrinsically stable MPC scheme where the orientation of the footsteps is chosen before determining their location and the CoM trajectory. The second solution, which represents the main contribution of the paper, is conceptually different: no high-level velocity is generated, and footstep orientations are chosen at the same time of the other decision variables in a singlestage MPC. This is made possible by carefully redesigning the motion constraints so as to preserve linearity. Preliminary results on a simulated NAO confirm that the single-stage method outperforms the conventional double-stage scheme.
基于单阶段MPC的仿人步行到运动步态生成
我们考虑了一个人形机器人的步态生成问题,该机器人必须步行到指定的笛卡尔目标。作为第一个解决方案,我们考虑了对我们之前工作的一个相当直接的改编:外部块产生高水平的速度,然后通过双级本质稳定的MPC方案进行跟踪,在确定其位置和CoM轨迹之前选择脚步的方向。第二种解决方案代表了本文的主要贡献,在概念上有所不同:在单阶段MPC中,不生成高水平速度,同时选择其他决策变量的脚步方向。这可以通过仔细重新设计运动约束以保持线性来实现。在模拟NAO上的初步结果证实了单级方法优于传统的双级方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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