Robust Locomotion Exploiting Multiple Balance Strategies

Robust Locomotion Exploiting Multiple Balance Strategies: An Observer-Based Cascaded Model Predictive Control Approach

Ding, J. (TU Delft Learning & Autonomous Control)
Han, Linyan (Southeast University)
Ge, Ligang (Ubtech Robotics Corporation)
Liu, Yizhang (Ubtech Robotics Corporation)
Pang, Jianxin (Ubtech Robotics Corporation)

2022

Robust locomotion is a challenging task for humanoid robots, especially when considering dynamic disturbances. This article proposes a disturbance observer-based cascaded model predictive control (MPC) approach for bipedal locomotion, with the capability of exploiting ankle, stepping, hip and height variation strategies. Specifically, based on the variable-height inverted pendulum model, a nonlinear MPC that is run at a low frequency is built for 3-D locomotion (i.e., with height variation) while accounting for the footstep modulation as well. Differing from previous works, the nonlinear MPC is formulated as a convex optimization problem by semidefinite relaxation. Subsequently, assuming a flywheel at the pelvis center, a linear MPC that is run at a high frequency is proposed to regulate angular momentum (e.g., through rotating the upper body), which is solved by convex quadratic programming. To run the cascaded MPC in a closed-loop manner, a high order sliding mode observer is designed to estimate system states and dynamic disturbances simultaneously. Simulation and hardware experiments demonstrate the walking robustness in real-world scenarios, including 3-D walking with varying speeds, walking across non-coplanar terrains and push recovery.

Bipedal locomotion
Computational modeling
convex optimization
disturbance observer
Foot
Hip
Legged locomotion
model predictive control
Predictive control
reactive walking
Solid modeling
Trajectory

http://resolver.tudelft.nl/uuid:3a4e3a7e-e7d4-4f16-a763-47bd3aff6796

https://doi.org/10.1109/TMECH.2022.3173805

2023-07-01

1083-4435

IEEE - ASME Transactions on Mechatronics, 27 (4), 2089-2097

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2022 J. Ding, Linyan Han, Ligang Ge, Yizhang Liu, Jianxin Pang