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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/24147

Title: Toward adaptive and intelligent electroadhesives for robotic material handling
Authors: Guo, Jianglong
Bamber, Tom
Zhao, Yuchen
Chamberlain, Matthew R.
Justham, Laura
Jackson, Michael R.
Keywords: Adaptive and intelligent electroadhesive
Electroadhesion
Electroadhesive design and manufacture
Grippers and other end-effectors
Material handling
Sensor-based control
Issue Date: 2017
Publisher: © The Authors. Published by the IEEE.
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.
Abstract: 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.
Description: 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/
Sponsor: This work was supported by the EPSRC Centre for Innovative Manufacturing in Intelligent Automation under Grant EP/IO33467/1.
Version: Published
DOI: 10.1109/LRA.2016.2646258
URI: https://dspace.lboro.ac.uk/2134/24147
Publisher Link: http://dx.doi.org/10.1109/LRA.2016.2646258
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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