线性模型竟可高效控制复杂腿式机器人运动，无需非线性计算。
The Surprising Effectiveness of Linear Models for Whole-Body Model-Predictive Control
- 用线性时不变模型近似全身动力学，实现高效控制。
- 在四足机器人上完成行走、抗扰与导航，无需步态规划器。
- 成功应用于液压人形机器人，应对惯性大、仿真到现实差距大的挑战。
当肢体运动控制器需要考虑非线性因素时？本工作表明，使用简单线性时不变近似全身动力学的全身体型模型预测控制器，能够使复杂腿式机器人完成基本运动任务。该方法无需在线进行非线性动力学计算或矩阵求逆。我们在四足机器人上实现了行走、抗扰及目标位置导航，且无需独立步态规划器。此外，我们还在一台具有显著肢体惯性、复杂执行器动力学和较大仿真到现实差异的液压人形机器人上实现了动态行走。
原文摘要 · Abstract (English)
When do locomotion controllers require reasoning about nonlinearities? In this work, we show that a whole-body model-predictive controller using a simple linear time-invariant approximation of the whole-body dynamics is able to execute basic locomotion tasks on complex legged robots. The formulation requires no online nonlinear dynamics evaluations or matrix inversions. We demonstrate walking, disturbance rejection, and even navigation to a goal position without a separate footstep planner on a quadrupedal robot. In addition, we demonstrate dynamic walking on a hydraulic humanoid, a robot with significant limb inertia, complex actuator dynamics, and large sim-to-real gap.
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