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Published Online: 12 December 2019

Bio-Inspired Shape-Adaptive Soft Robotic Grippers Augmented with Electroadhesion Functionality

Publication: Soft Robotics
Volume 6, Issue Number 6

Abstract

Soft robotic grippers (SRGs) have been extensively employed in robotic grasping and manipulation applications due to the fact that they are beneficial for pick-and-place of difficult-to-handle and delicate objects with various geometries and stiffness in a comfortable and safer way. This article presents a bio-inspired and shape-adaptive SRG augmented with electroadhesion (EA) functionality, FinEA, by a cost-effective combination of a Fin Ray structured two-fingered SRG with two soft-stretchable EA pads. The EA pads were manufactured by screen printing a layer of electrically conductive and elastomeric carbon black powder mixed with polydimethylsiloxane onto a dielectric substrate. The compliant Fin Ray fingers, composed of soft longitudinal beams and rigid cross beams, were structurally optimized by the finite element method using ABAQUS/CAE based on three key parameters: the open angle of the longitudinal beams, the spacing between the cross beams, and the incline angle of the cross beams. The soft beams were produced by a traditional soft lithography method, whereas the rigid cross beams were three-dimensionally printed. The resultant FinEA grippers were capable of lifting not only flat/thin materials without distorting them due to the employment of EA, but also concave and convex objects due to the passively shape-adaptive Fin Ray structure and the EA functionality. In addition, the proposed FinEA grippers were able to grasp delicate materials and objects whose diameters are larger than the overall gripper length. Furthermore, 65% more weight in shear were picked up by the FinEA gripper when 4 kV was applied compared with 0 V. The FinEA concept provides useful and alternative solution for controllable adhesion-based SRGs and may facilitate the inspiration and development of future SRGs with added functionality and enhanced versatility.

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Information

Published In

cover image Soft Robotics
Soft Robotics
Volume 6Issue Number 6December 2019
Pages: 701 - 712
PubMed: 31329029

History

Published online: 12 December 2019
Published in print: December 2019
Published ahead of print: 18 July 2019

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State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
Ruizhou Song
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
Zhuo Zhang
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
Long Bai
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
Fuqiang Liu
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
Pei Jiang
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
Dirk Sindersberger
Mechatronics Research Unit, OTH Regensburg, Regensburg, Germany.
Gareth J. Monkman
Mechatronics Research Unit, OTH Regensburg, Regensburg, Germany.
Jianglong Guo
SoftLab, Bristol Robotics Laboratory, University of Bristol, Bristol, United Kingdom.

Notes

Address correspondence to: Rui Chen, State Key Laboratory of Mechanical Transmissions, Chongqing University, 174 Shapingba Zhengjie, Chongqing 400044, China [email protected]

Author Disclosure Statement

No competing financial interests exist.

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