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Vibration Characteristics Analysis of Human- Robot Coupled System for Walking Posture of Elderly-Assistant Robot

Authors :
Xiaodong Zhang
Xiaoqi Mu
Haipeng Xu
Ahmad B. Alhassan
Hamza K. Kadry
Source :
IEEE Access, Vol 9, Pp 44217-44235 (2021)
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

The ever-increasing need for nursing care due to the aging population necessitates the need for safe and efficient elder-assistant robots that can reduce the care burden on the societies. However, most of the existing studies focus only on the robot-user sitting posture. In this paper, the vibration characteristics of the human-robot coupled system for the walking posture of the elderly-assistant robot is analyzed. The work is particularly important as it assesses the possible resonance, which if present, will adversely affect the comfort of the elderly. Initially, the dynamic model of the human-robot coupled system is derived. Then, the modal analysis of the robot is carried out to assess the possible resonance of the system during walking. Thirdly, MATLAB software is used for the vibration simulation analysis of the human-robot coupled model under different scenarios, namely, sudden impact and uneven road situations. Moreover, real-time experiments are conducted on the lab-scale robot to verify the effectiveness of the derived model under the same road conditions. Finally, the sensitivity analysis of the vibration responses to the damping ratio, mass ratios, and the natural frequencies is conducted to assess the effects of the parameters on the vibration responses. The simulation and the real-time analysis show that the model can be effectively used to assess the road-robot-human vibration transmissibility, particularly human hand comfort. Thus, the results demonstrate that the designed robot can be safely used by the elderly as it does not resonate during walking.

Details

Language :
English
ISSN :
21693536
Volume :
9
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.65404b19395a4e909c9e1483f3848e1b
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2021.3066397