Parameterized gait pattern generator based on linear inverted pendulum model with natural ZMP references. (2017)

• Record Type: Journal Article
• Authors: Ho, Ya-Fang; Li, Tzuu-Hseng S.; Kuo, Ping-Huan; Ye, Yan-Ting
• Is Part Of: Knowledge engineering review. Volume 32(2017)
• Publication Date: 2017
• Subjects: Expert systems (Computer science) -- Periodicals; 006.33
• DOI: 10.1017/S0269888916000138
• Languages: English
• ISSNs: 0269-8889

Abstract

Abstract: 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.