为足式机器人运动控制器提供稳定性保证，提升抗扰能力。
Adaptive Non-linear Centroidal MPC with Stability Guarantees for Robust Locomotion of Legged Robots
- 基于自适应控制重构模型预测控制器，实现闭环稳定
- 在未知负载和恒定干扰下仍保持稳定，实测有效
- 适用于人形与四足机器人，通用性强
基于简化质心动力学的非线性模型预测运动控制器在足式机器人中已广泛应用。尽管存在动力学简化假设，这类方法已被证明可应对小推力扰动并具备一定鲁棒性，尤其在参数不确定（如未知负载）时表现良好。本文通过重构质心模型预测控制器，结合自适应控制与控制李雅普诺夫函数的思想，首次为该类控制器提供了严格的闭环稳定性证明。新方法还对一类未测量的恒定扰动具备鲁棒性。为验证方法普适性，我们在新一代人形机器人ergoCub（56.7 kg）及商用四足机器人Aliengo（21 kg）上完成了验证。
原文摘要 · Abstract (English)
Nonlinear model predictive locomotion controllers based on the reduced centroidal dynamics are nowadays ubiquitous in legged robots. These schemes, even if they assume an inherent simplification of the robot's dynamics, were shown to endow robots with a step-adjustment capability in reaction to small pushes, and, moreover, in the case of uncertain parameters - as unknown payloads - they were shown to be able to provide some practical, albeit limited, robustness. In this work, we provide rigorous certificates of their closed loop stability via a reformulation of the centroidal MPC controller. This is achieved thanks to a systematic procedure inspired by the machinery of adaptive control, together with ideas coming from Control Lyapunov functions. Our reformulation, in addition, provides robustness for a class of unmeasured constant disturbances. To demonstrate the generality of our approach, we validated our formulation on a new generation of humanoid robots - the 56.7 kg ergoCub, as well as on a commercially available 21 kg quadruped robot, Aliengo.
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