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

Research output: Contribution to journalArticlepeer-review


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 languageEnglish
Pages (from-to)159507 - 159518
Number of pages12
JournalIEEE Access
Publication statusPublished - 28 Oct 2019


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