Abstract This paper addresses the push recovery of quadruped robots trotting on even terrain. Push recovery is the ability of a legged robot to maintain its balance in the presence of sudden external forces applied to the robot. Due to the nature of this dynamical gait, the quadruped robot can be modeled as a biped robot where each two cross legs of the quadruped are modeled as a virtual leg. Then, the virtual biped model is further reduced to a two-dimensional linear inverted pendulum plus flywheel model (LIPFM). Moreover, using the concept of capture points for the biped model, the desired locations for the center of pressure (COP) of the legs for recovering the robot's balance are calculated by designing a two-dimensional dynamic capture point estimator. A model-based predictive controller (MPC) is then proposed to adjust the footstep locations and generate a new walking-pattern. The resulting redesigned joint angles for the virtual biped model are then transformed back to those of the actual quadruped model. Simulation results show the effectiveness of the proposed method.

中文翻译：

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基于 MPC 的四足机器人小跑步态二维推力恢复及其简化虚拟模型

摘要 本文讨论了在平坦地形上小跑的四足机器人的推动恢复。推力恢复是腿式机器人在突然施加外力的情况下保持平衡的能力。由于这种动态步态的性质，四足机器人可以建模为双足机器人，其中四足机器人的每两条交叉腿都被建模为一条虚拟腿。然后，将虚拟双足模型进一步简化为二维线性倒立摆加飞轮模型（LIPFM）。此外，利用双足模型捕获点的概念，通过设计二维动态捕获点估计器来计算用于恢复机器人平衡的腿部压力中心（COP）的所需位置。然后提出了基于模型的预测控制器 (MPC) 来调整足迹位置并生成新的步行模式。为虚拟两足动物模型重新设计的关节角度然后被转换回实际四足动物模型的关节角度。仿真结果表明了该方法的有效性。