Adaptive Non-linear Centroidal MPC with Stability Guarantees for Robust Locomotion of Legged Robots
This work addresses the lack of stability certificates in widely-used centroidal MPC controllers for legged robots, offering a theoretically grounded improvement.
The authors reformulate centroidal MPC for legged robots to provide rigorous closed-loop stability guarantees and robustness to unmeasured constant disturbances, validated on a 56.7 kg humanoid and a 21 kg quadruped.
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.