Adaptive Non-Linear Centroidal MPC With Stability Guarantees for Robust Locomotion of Legged Robots

作     者：Elobaid, Mohamed Turrisi, Giulio Rapetti, Lorenzo Romualdi, Giulio Dafarra, Stefano Kawakami, Tomohiro Chaki, Tomohiro Yoshiike, Takahide Semini, Claudio Pucci, Daniele 

作者机构：Ist Italiano Tecnol IIT Artificial & Mech Intelligence AMI I-16163 Genoa Italy Ist Italiano Tecnol IIT Dynam Legged Syst DLS I-16163 Genoa Italy Honda R&D Frontier Robot Innovat Res Excellence Saitama 3510188 Japan Univ Manchester Machine Learning & Optimisat Manchester M13 9PL England 

出 版 物：《IEEE ROBOTICS AND AUTOMATION LETTERS》 (IEEE Robot. Autom.)

年 卷 期：2025年第10卷第3期

页      面：2806-2813页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 

基　　金：Italian National Institute for Insurance against Accidents at Work (INAIL) Honda Research and Development Japan 

主　　题：Robots Robustness Trajectory Payloads Legged locomotion Humanoid robots Vectors Robot kinematics Quadrupedal robots Predictive models Legged robots robust/adaptive control optimization and optimal control 

摘      要：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 in the case of uncertain parameters - as unknown payloads - they were shown to provide some practical, albeit limited, robustness. In this work, we provide rigorous certificates of their closed-loop stability via reformulating the online 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 $\text{56.7 kg}$ ergoCub, as well as on the commercially available $\text{21 kg}$ quadruped robot Aliengo.