z-logo
open-access-imgOpen Access
Suppression of Quadruped Robot Body Disturbance by Virtual Spring-Damping Model
Author(s) -
JingYe He,
Junpeng Shao,
Bingwei Gao,
BingYi Miao,
Xuan Shao
Publication year - 2022
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2022/4510678
Subject(s) - control theory (sociology) , trajectory , kinematics , robot , disturbance (geology) , computer science , displacement (psychology) , spring (device) , simulation , stability (learning theory) , engineering , physics , artificial intelligence , structural engineering , geology , classical mechanics , psychology , paleontology , control (management) , astronomy , machine learning , psychotherapist
The quadruped robot is subject to self and external interference during the running process. In this paper, in order to improve the stability of the quadruped robot, a disturbance suppression strategy based on the kinematic model and the virtual model is proposed. Through the whole-body kinematics modeling of the body, the cause of the disturbance is analyzed. At the same time, two spring-damping virtual elements are introduced on the body. The virtual force generated by the spring-damping model is according to the displacement and speed of the CoM (center of mass) when the robot is moving. By simulating the tort gait of the robot, sorting out the data obtained from the experiment, and drawing a comparison curve with the experiment results of the no spring-damping virtual element under the same conditions, it is proved that the method proposed in this paper has a significant effect on maintaining the dynamic stability of the body, and the actual trajectory is not different from the theoretical trajectory.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom