A scalable variable stiffness revolute joint based on layer jamming for robotic exoskeletons
File(s)TAROS2020_022_major_v2.pdf (988.29 KB)
Accepted version
Author(s)
Shen, Matthew
Clark, Angus
Rojas, Nicolas
Type
Conference Paper
Abstract
Robotic exoskeletons have been a focal point of research due to an ever-increasing ageing population, longer life expectancy, and a desire to further improve the existing capabilities of humans. However, their effectiveness is often limited, with strong rigid structures poorly interfacing with humans and soft flexible mechanisms providing limited forces. In this paper, a scalable variable stiffness revolute joint is proposed to overcome this problem. By using layer jamming, the joint has the ability to stiffen or soften for different use cases. A theoretical and experimental study of maximum stiffness with size was conducted to determine the suitability and scalablity of this technology. Three sizes (50 mm, 37.5 mm, 25 mm diameter) of the joint were developed and evaluated. Results indicate that this technology is most suitable for use in human fingers, as the prototypes demonstrate a sufficient torque (0.054 Nm) to support finger movement.
Date Issued
2020-12-03
Date Acceptance
2020-05-11
Citation
Lecture Notes in Computer Science, 2020, 12228, pp.3-14
ISSN
0302-9743
Publisher
Springer Verlag
Start Page
3
End Page
14
Journal / Book Title
Lecture Notes in Computer Science
Volume
12228
Copyright Statement
© 2020 Springer Nature Switzerland AG. The final authenticated version is available online at https://doi.org/10.1007/978-3-030-63486-5_1
Source
Towards Autonomous Robotic Systems Conference ( TAROS ) 2020
Subjects
Artificial Intelligence & Image Processing
Publication Status
Published
Start Date
2020-09-16
Finish Date
2020-09-16
Coverage Spatial
Nottingham, UK (online)
Date Publish Online
2020-12-03