Parameterized gait pattern generator based on linear inverted pendulum model with natural ZMP references

Ya Fang Ho, Tzuu-Hseng S. Li, Ping Huan Kuo, Yan Ting Ye

研究成果: Article

6 引文 斯高帕斯(Scopus)

摘要

This paper presents a parameterized gait generator based on linear inverted pendulum model (LIPM) theory, which allows users to generate a natural gait pattern with desired step sizes. Five types of zero moment point (ZMP) components are proposed for formulating a natural ZMP reference, where ZMP moves continuously during single support phases instead of staying at a fixed point in the sagittal and lateral plane. The corresponding center of mass (CoM) trajectories for these components are derived by LIPM theory. To generate a parameterized gait pattern with user-defined parameters, a gait planning algorithm is proposed, which determines related coefficients and boundary conditions of the CoM trajectory for each step. The proposed parameterized gait generator also provides a concept for users to generate gait patterns with self-defined ZMP references by using different components. Finally, the feasibility of the proposed method is validated by the experimental results with a teen-sized humanoid robot, David, which won first place in the sprint event at the 20th Federation of International Robot-soccer Association (FIRA) RoboWorld Cup.

原文English
文章編號e3
期刊Knowledge Engineering Review
32
DOIs
出版狀態Published - 2016 八月 4

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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