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Toward adaptive and intelligent electroadhesives for robotic material handling

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journal contribution
posted on 16.02.2017, 13:39 authored by Jianglong Guo, Thomas Bamber, Yuchen Zhao, Matthew Chamberlain, Laura JusthamLaura Justham, Michael R. Jackson
An autonomous, adaptive, and intelligent electroadhesive material handling system has been presented in this paper. The system has been proposed and defined based on the identification of a system need through a comprehensive literature review and laboratory-based experimental tests. The proof of the proposed concept has been implemented by a low cost and novel electroadhesive pad design and manufacture process, and a mechatronic and reconfigurable platform, where force, humidity, and capacitive sensors have been employed. This provides a solution to an autonomous elelctroadhesive material handling system that is environmentally and substrate material adaptive. The results have shown that the minimum voltage can be applied to robustly grasp different materials under different environment conditions. The proposed system is particularly useful for pick-and-place applications where various types of materials and changing environments exist such as robotic material handling applications in the textile and waste recycling industry.

Funding

This work was supported by the EPSRC Centre for Innovative Manufacturing in Intelligent Automation under Grant EP/IO33467/1.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Robotics and Automation Letters

Volume

2

Issue

2

Pages

538 - 545

Citation

GUO, J. ...et al., 2017. Toward adaptive and intelligent electroadhesives for robotic material handling. IEEE Robotics and Automation Letters, 2(2), pp. 538-545.

Publisher

© The Authors. Published by the IEEE.

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

Publication date

2016-12-28

Notes

This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

eISSN

2377-3774

Language

en