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Robust Walking for Humanoid Robot Based on Divergent Component of Motion.

Authors :
Zhang Z
Zhang L
Xin S
Xiao N
Wen X
Source :
Micromachines [Micromachines (Basel)] 2022 Jul 11; Vol. 13 (7). Date of Electronic Publication: 2022 Jul 11.
Publication Year :
2022

Abstract

In order to perform various complex tasks in place of humans, humanoid robots should walk robustly in the presence of interference. In the paper, an improved model predictive control (MPC) method based on the divergent components of motion (DCM) is proposed. Firstly, the humanoid robot model is simplified to a finite-sized foot-pendulum model. Then, the gait of the humanoid robot in the single-support phase (SSP) and double-support phase (DSP) is planned based on DCM. The center of mass (CoM) of the robot will converge to the DCM, which simplifies the feedback control process. Finally, an MPC controller incorporating an extended Kalman filter (EKF) is proposed to realize the tracking of the desired DCM trajectory. By adjusting the step duration, the controller can compensate for CoM trajectory errors caused by disturbances. Simulation results show that-compared with the traditional method-the method we propose achieves improvements in both disturbed walking and uneven-terrain walking.

Details

Language :
English
ISSN :
2072-666X
Volume :
13
Issue :
7
Database :
MEDLINE
Journal :
Micromachines
Publication Type :
Academic Journal
Accession number :
35888912
Full Text :
https://doi.org/10.3390/mi13071095