Joints with angle dependent damping can help to reduce impact forces in robots
File(s)
Published version
Author(s)
Perera, Shehara
Bornassi, Saeed
Ghajari, Mazdak
Nanayakkara, Thrishantha
Type
Journal Article
Abstract
This paper investigates how a new angle-dependent damper design can help a robot to reduce collision
forces. We designed a fluid-viscous angle-dependent damper by smoothly changing the clearance
between the stationary and moving parts. Analytical and numerical simulation-based predictions
were experimentally tested. Analytical modelling shows that angle-dependent damping has a 48%
reduction in peak forces when compared to constant damping. Numerical simulations show that
variable-gap dampers can change damping by 134× during a 10× gap change. The experimental
findings confirm the analytical predictions by reducing collision force by up to 10%. These findings
suggest that the angle-dependent variable damping solution could be used for robots that experience
collisions such as industrial robotic manipulators, legged robots, perching robots, or robots that catch
moving objects.
forces. We designed a fluid-viscous angle-dependent damper by smoothly changing the clearance
between the stationary and moving parts. Analytical and numerical simulation-based predictions
were experimentally tested. Analytical modelling shows that angle-dependent damping has a 48%
reduction in peak forces when compared to constant damping. Numerical simulations show that
variable-gap dampers can change damping by 134× during a 10× gap change. The experimental
findings confirm the analytical predictions by reducing collision force by up to 10%. These findings
suggest that the angle-dependent variable damping solution could be used for robots that experience
collisions such as industrial robotic manipulators, legged robots, perching robots, or robots that catch
moving objects.
Date Issued
2025-08-05
Date Acceptance
2025-07-21
Citation
Scientific Reports, 2025, 15
ISSN
2045-2322
Publisher
Nature Portfolio
Journal / Book Title
Scientific Reports
Volume
15
Copyright Statement
© The Author(s) 2025 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Publication Status
Published
Article Number
28578
Date Publish Online
2025-08-05