Robust bipedal locomotion control based on model predictive control and divergent component of motion

In this paper, previous works on the Model Predictive Control (MPC) and the Divergent Component of Motion (DCM) for bipedal walking control are extended. To this end, we employ a single MPC which uses a combination of Center of Pressure (CoP) manipulation, step adjustment, and Centroidal Moment Pivo...

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Bibliographic Details
Published in2017 IEEE International Conference on Robotics and Automation (ICRA) pp. 3505 - 3510
Main Authors Shafiee-Ashtiani, Milad, Yousefi-Koma, Aghil, Shariat-Panahi, Masoud
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.05.2017
Subjects
Humanoid robots
Legged locomotion
Mathematical model
Modulation
Robustness
Trajectory
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DOI10.1109/ICRA.2017.7989401

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Summary:In this paper, previous works on the Model Predictive Control (MPC) and the Divergent Component of Motion (DCM) for bipedal walking control are extended. To this end, we employ a single MPC which uses a combination of Center of Pressure (CoP) manipulation, step adjustment, and Centroidal Moment Pivot (CMP) modulation to design a robust walking controller. Furthermore, we exploit the concept of time-varying DCM to generalize our walking controller for walking in uneven surfaces. Using our scheme, a general and robust walking controller is designed which can be implemented on robots with different control authorities, for walking on various environments, e.g. uneven terrains or surfaces with a very limited feasible area for stepping. The effectiveness of the proposed approach is verified through simulations on different scenarios and comparison to the state of the art.
DOI:10.1109/ICRA.2017.7989401