Online Non-linear Centroidal MPC for Humanoid Robots Payload Carrying with Contact-Stable Force Parametrization

Abstract

In this paper we consider the problem of allowing a humanoid robot that is subject to a persistent disturbance, in the form of a payload-carrying task, to follow given planned footsteps. To solve this problem, we combine an online nonlinear centroidal Model Predictive Controller - MPC with a contact stable force parametrization. The cost function of the MPC is augmented with terms handling the disturbance and regularizing the parameter. The performance of the resulting controller is validated both in simulations and on the humanoid robot iCub. Finally, the effect of using the parametrization on the computational time of the controller is briefly studied.

References in corpus (4)

• Walking Stabilization Using Step Timing and Location Adjustment on the Humanoid Robot, Atlas
• Adaptive CLF-MPC With Application To Quadrupedal Robots
• iCub3 Avatar System: Enabling Remote Fully-Immersive Embodiment of Humanoid Robots
• A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots

Cited by in corpus (1)

• Adaptive Non-linear Centroidal MPC with Stability Guarantees for Robust Locomotion of Legged Robots