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Fuzzy-logic zero-moment-point trajectory generation for reduced trunk motions of biped robots

机译：减少两足机器人躯干运动的模糊逻辑零矩点轨迹生成

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摘要

Trunk motions are typically used in biped robots to stabilize the locomotion. However, they can be very large for some leg trajectories unless they are carefully designed. This paper proposes a fuzzy-logic zero-moment-point (ZMP) trajectory generator that would eventually reduce the swing motion of the trunk significantly even though the leg trajectory is casually designed, for example, simply to avoid obstacles. The fuzzy-logic ZMP trajectory generator uses the leg trajectory as an input. The resulting ZMP trajectory is similar to that of a human one and continuously moves forward in the direction of the locomotion. The trajectory of the trunk to stabilize the locomotion is determined by solving a differential equation with the ZMP trajectory and the leg trajectory known. The proposed scheme is simulated on a 7-DOF biped robot in the sagittal plane. The simulation results show that the ZMP trajectory generated by the proposed fuzzy-logic generator increases the stability of the locomotion and thus reduces the motion range of the trunk significantly.
机译：两足动物机器人通常使用躯干运动来稳定运动。但是，对于某些腿部轨迹，它们可能会很大，除非对其进行了精心设计。本文提出了一种模糊逻辑零矩点（ZMP）轨迹生成器，该轨迹生成器最终将显着降低躯干的摆动运动，即使是随意设计腿部轨迹（例如，仅仅是为了避免障碍物）。模糊逻辑ZMP轨迹生成器使用腿轨迹作为输入。产生的ZMP轨迹类似于人类的轨迹，并且在运动方向上连续向前移动。通过求解具有ZMP轨迹和腿部轨迹的微分方程来确定躯干的轨迹，以稳定运动。在矢状面上的7自由度Biped机器人上对提出的方案进行了仿真。仿真结果表明，所提出的模糊逻辑发生器产生的ZMP轨迹增加了运动的稳定性，从而显着减小了躯干的运动范围。

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