论文标题
具有非线性模型预测控制的平面两足动力：使用全身动力学的在线步态生成
Planar Bipedal Locomotion with Nonlinear Model Predictive Control: Online Gait Generation using Whole-Body Dynamics
论文作者
论文摘要
对于具有输入约束和未成熟的双皮亚机器人实时生成动态步行的能力，有可能在动态，复杂和非结构化的环境中实现运动。然而，两足机器人的高维质将全阶刚体动力学的使用限制为离线合成的步态，然后在线跟踪。在这项工作中，我们开发了一种在线非线性模型预测控制方法，该方法利用全阶动态来实现各种步行行为。此外，这种方法可以与步态通过所需的参考结合起来，以实现较短的预测范围和快速的在线重新计划，从而弥合了在线反应性控制和离线步态计划之间的差距。我们在模拟和硬件上的平面机器人3M上，在平面机器人Amber-3M上演示了所提出的方法。
The ability to generate dynamic walking in real-time for bipedal robots with input constraints and underactuation has the potential to enable locomotion in dynamic, complex and unstructured environments. Yet, the high-dimensional nature of bipedal robots has limited the use of full-order rigid body dynamics to gaits which are synthesized offline and then tracked online. In this work we develop an online nonlinear model predictive control approach that leverages the full-order dynamics to realize diverse walking behaviors. Additionally, this approach can be coupled with gaits synthesized offline via a desired reference to enable a shorter prediction horizon and rapid online re-planning, bridging the gap between online reactive control and offline gait planning. We demonstrate the proposed method, both with and without an offline gait, on the planar robot AMBER-3M in simulation and on hardware.
