论文标题
无表示模型的预测控制四足动物的动态运动
Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds
论文作者
论文摘要
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（3D）空间中四足动物的各种动态运动。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（QP）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，包括周期性四足步骤和受控的后空验证，我们的控制策略可以稳定涉及3D演习中奇异性的动态运动。
This paper presents a novel Representation-Free Model Predictive Control (RF-MPC) framework for controlling various dynamic motions of a quadrupedal robot in three dimensional (3D) 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 (QP) 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 3D maneuvers.
