On-Line Gait Adjustment for Humanoid Robot Robust Walking Based on Divergence Component of Motion

Sheng Dong; Zhaohui Yuan; Xiaojun Yu; Jianrui Zhang; Muhammad Tariq Sadiq; Fuli Zhang

doi:10.1109/ACCESS.2019.2949747

On-Line Gait Adjustment for Humanoid Robot Robust Walking Based on Divergence Component of Motion

Sheng Dong, Zhaohui Yuan, Xiaojun Yu, Jianrui Zhang, Muhammad Tariq Sadiq, Fuli Zhang

School of Arch, Tech and Eng

Research output: Contribution to journal › Article › peer-review

Abstract

As the first step for biped robots to enter the human life, robust walking is a difficult problem to be solved owing to the various algorithms and practical engineering issues being involved. This paper studies the robust walking problem for humanoid robots by using the divergence component of motion (DCM) method based on linear inverted pendulum model. Firstly, we implement a DCM trajectory planning method to simplify the planning process. It calculates the DCM trajectories under the requirements of walking speed and initial state of the system. Then, a DCM feedback controller with anti-disturbance ability is proposed to realize the tracking control of the planned trajectory. Finally, the optimization method and DCM feedback control are integrated into a hybrid optimization controller, which takes into account the step adjustment and the step duration adjustment of the robot. Simulation results demonstrates that the technique can act naturally stable inside an enormous scope of effect unsettling influences, the maximum recoverable impact of a humanoid robots with a mass of 70Kg can reach 85Ns, which is much better than the 20Ns of the existing model-based prediction control method.

Original language	English
Article number	8884092
Pages (from-to)	159507 - 159518
Number of pages	12
Journal	IEEE Access
Volume	7
DOIs	https://doi.org/10.1109/ACCESS.2019.2949747
Publication status	Published - 28 Oct 2019

Bibliographical note

Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61705184 and Grant 51875477, in part by the Natural Science Basic Research Plan in Shaanxi Province of China under Grant 2018JQ6014, in part by the Fundamental Research Funds for the Central Universities under Grant G2018KY0308, in part by the China Postdoctoral Science Foundation under Grant 2018M641013, in part by the Training Project of Postgraduate Innovation Competition Team in Northwestern Polytechnical University, in part by the Doctoral Fund Project of Longdong University under Grant XYBY1901, and in part by the Higher Education Innovative Ability Enhancement Project of Gansu Province under Grant 2019A-113.

Publisher Copyright:
© 2013 IEEE.

Keywords

adaptive step duration
Biped robot
divergence component of motion (DCM)
gait generation
humanoid robot

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10.1109/ACCESS.2019.2949747Licence: CC BY

Cite this

@article{0e21150d04b24b6a859b30a01e5912a7,

title = "On-Line Gait Adjustment for Humanoid Robot Robust Walking Based on Divergence Component of Motion",

abstract = "As the first step for biped robots to enter the human life, robust walking is a difficult problem to be solved owing to the various algorithms and practical engineering issues being involved. This paper studies the robust walking problem for humanoid robots by using the divergence component of motion (DCM) method based on linear inverted pendulum model. Firstly, we implement a DCM trajectory planning method to simplify the planning process. It calculates the DCM trajectories under the requirements of walking speed and initial state of the system. Then, a DCM feedback controller with anti-disturbance ability is proposed to realize the tracking control of the planned trajectory. Finally, the optimization method and DCM feedback control are integrated into a hybrid optimization controller, which takes into account the step adjustment and the step duration adjustment of the robot. Simulation results demonstrates that the technique can act naturally stable inside an enormous scope of effect unsettling influences, the maximum recoverable impact of a humanoid robots with a mass of 70Kg can reach 85Ns, which is much better than the 20Ns of the existing model-based prediction control method.",

keywords = "adaptive step duration, Biped robot, divergence component of motion (DCM), gait generation, humanoid robot",

author = "Sheng Dong and Zhaohui Yuan and Xiaojun Yu and Jianrui Zhang and Sadiq, {Muhammad Tariq} and Fuli Zhang",

note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grant 61705184 and Grant 51875477, in part by the Natural Science Basic Research Plan in Shaanxi Province of China under Grant 2018JQ6014, in part by the Fundamental Research Funds for the Central Universities under Grant G2018KY0308, in part by the China Postdoctoral Science Foundation under Grant 2018M641013, in part by the Training Project of Postgraduate Innovation Competition Team in Northwestern Polytechnical University, in part by the Doctoral Fund Project of Longdong University under Grant XYBY1901, and in part by the Higher Education Innovative Ability Enhancement Project of Gansu Province under Grant 2019A-113. Publisher Copyright: {\textcopyright} 2013 IEEE.",

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AU - Zhang, Jianrui

AU - Sadiq, Muhammad Tariq

AU - Zhang, Fuli

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N2 - As the first step for biped robots to enter the human life, robust walking is a difficult problem to be solved owing to the various algorithms and practical engineering issues being involved. This paper studies the robust walking problem for humanoid robots by using the divergence component of motion (DCM) method based on linear inverted pendulum model. Firstly, we implement a DCM trajectory planning method to simplify the planning process. It calculates the DCM trajectories under the requirements of walking speed and initial state of the system. Then, a DCM feedback controller with anti-disturbance ability is proposed to realize the tracking control of the planned trajectory. Finally, the optimization method and DCM feedback control are integrated into a hybrid optimization controller, which takes into account the step adjustment and the step duration adjustment of the robot. Simulation results demonstrates that the technique can act naturally stable inside an enormous scope of effect unsettling influences, the maximum recoverable impact of a humanoid robots with a mass of 70Kg can reach 85Ns, which is much better than the 20Ns of the existing model-based prediction control method.

AB - As the first step for biped robots to enter the human life, robust walking is a difficult problem to be solved owing to the various algorithms and practical engineering issues being involved. This paper studies the robust walking problem for humanoid robots by using the divergence component of motion (DCM) method based on linear inverted pendulum model. Firstly, we implement a DCM trajectory planning method to simplify the planning process. It calculates the DCM trajectories under the requirements of walking speed and initial state of the system. Then, a DCM feedback controller with anti-disturbance ability is proposed to realize the tracking control of the planned trajectory. Finally, the optimization method and DCM feedback control are integrated into a hybrid optimization controller, which takes into account the step adjustment and the step duration adjustment of the robot. Simulation results demonstrates that the technique can act naturally stable inside an enormous scope of effect unsettling influences, the maximum recoverable impact of a humanoid robots with a mass of 70Kg can reach 85Ns, which is much better than the 20Ns of the existing model-based prediction control method.

KW - adaptive step duration

KW - Biped robot

KW - divergence component of motion (DCM)

KW - gait generation

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JF - IEEE Access

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On-Line Gait Adjustment for Humanoid Robot Robust Walking Based on Divergence Component of Motion

Abstract

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Keywords

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