Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds
Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds
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DOI：
10.1109/tro.2020.3046415
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发表时间：
2021-08-01
影响因子：
7.8
通讯作者：
Park, Hae-Won
中科院分区：
文献类型：
--
作者：
Ding, Yanran;Pandala, Abhishek;Park, Hae-Won
本文介绍了一个新颖的无表示模型预测控制（RF-MPC）框架，用于控制三维（3-D）空间中四倍体机器人的各种动态运动。我们的公式使用旋转矩阵直接表示旋转动力学，这使我们摆脱了与使用欧拉角和四元素作为方向表示相关的问题。通过基于变异的线性化方案和精心构建的成本函数，MPC控制定律被转录为标准二次程序表格。 MPC控制器可以在四倍的机器人上以250 Hz的实时速率运行。实验结果，包括周期性四足步态和受控的后空浮动，我们的控制策略可以稳定涉及3-D手术中奇异性的动态运动。
This article presents a novel representation-free model predictive control (RF-MPC) framework for controlling various dynamic motions of a quadrupedal robot in three-dimensional (3-D) space. Our formulation directly represents the rotational dynamics using the rotation matrix, which liberates us from the issues associated with the use of Euler angles and quaternion as the orientation representations. With a variation-based linearization scheme and a carefully constructed cost function, the MPC control law is transcribed to the standard quadratic program form. The MPC controller can operate at real-time rates of 250 Hz on a quadruped robot. Experimental results including periodic quadrupedal gaits and a controlled backflip validate that our control strategy could stabilize dynamic motions that involve singularity in 3-D maneuvers.