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Data-driven bending angle prediction of soft pneumatic actuators with embedded flex sensors
conference contribution
posted on 2016-10-07, 09:08 authored by Khaled Elgeneidy, Niels LohseNiels Lohse, Michael JacksonIn this paper, resistive flex sensors have been embedded at the strain limiting layer of soft
pneumatic actuators, in order to provide sensory feedback that can be utilised in predicting their bending
angle during actuation. An experimental setup was prepared to test the soft actuators under controllable
operating conditions, record the resulting sensory feedback, and synchronise this with the actual bending
angles measured using a developed image processing program. Regression analysis and neural networks
are two data-driven modelling techniques that were implemented and compared in this study, to evaluate
their ability in predicting the bending angle response of the tested soft actuators at different input
pressures and testing orientations. This serves as a step towards controlling this class of soft bending
actuators, using data-driven empirical models that lifts the need for complex analytical modelling and
material characterisation. The aim is to ultimately create a more controllable version of this class of soft
pneumatic actuators with embedded sensing capabilities, to act as compliant soft gripper fingers that can
be used in applications requiring both a ‘soft touch’ as well as more controllable object manipulation.
Funding
The reported work has been partially funded by the EPSRC Centre for Innovated Manufacturing in Intelligent Automation (EP/IO33467/1).
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
IFAC Mechatronics 2016Citation
ELGENEIDY, K., LOHSE, N. and JACKSON, M., 2016. Data-driven bending angle prediction of soft pneumatic actuators with embedded flex sensors. IFAC-PapersOnLine, 49(21), pp.513-520.Publisher
© IFAC. Hosting by Elsevier Ltd.Version
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2016-01-01Publication date
2016Notes
This paper was presented at MECHATRONICS 2016: 7th IFAC Symposium on Mechatronic Systems & 15th Mechatronics Forum International Conference Loughborough University 5th - 8th September 2016.ISSN
2405-8963Publisher version
Language
- en