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Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning

Soft grippers with soft and flexible materials have been widely researched to improve the functionality of grasping. Although grippers that can grasp various objects with different shapes are important, a large number of industrial applications require a gripper that is targeted for a specified obje...

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Autores principales: Lee, Jun-Young, Eom, Jaemin, Yu, Sung Yol, Cho, Kyujin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805940/
https://www.ncbi.nlm.nih.gov/pubmed/33501280
http://dx.doi.org/10.3389/frobt.2020.00114
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author Lee, Jun-Young
Eom, Jaemin
Yu, Sung Yol
Cho, Kyujin
author_facet Lee, Jun-Young
Eom, Jaemin
Yu, Sung Yol
Cho, Kyujin
author_sort Lee, Jun-Young
collection PubMed
description Soft grippers with soft and flexible materials have been widely researched to improve the functionality of grasping. Although grippers that can grasp various objects with different shapes are important, a large number of industrial applications require a gripper that is targeted for a specified object. In this paper, we propose a design methodology for soft grippers that are customized to grasp single dedicated objects. A customized soft gripper can safely and efficiently grasp a dedicated target object with lowered surface contact forces while maintaining a higher lifting force, compared to its non-customized counterpart. A simplified analytical model and a fabrication method that can rapidly customize and fabricate soft grippers are proposed. Stiffness patterns were implemented onto the constraint layers of pneumatic bending actuators to establish actuated postures with irregular bending curvatures in the longitudinal direction. Soft grippers with customized stiffness patterns yielded higher shape conformability to target objects than non-patterned regular soft grippers. The simplified analytical model represents the pneumatically actuated soft finger as a summation of interactions between its air chambers. Geometric approximations and pseudo-rigid-body modeling theory were employed to build the analytical model. The customized soft grippers were compared with non-patterned soft grippers by measuring their lifting forces and contact forces while they grasped objects. Under the identical actuating pressure, the conformable grasping postures enabled customized soft grippers to have almost three times the lifting force than that of non-patterned soft grippers, while the maximum contact force was reduced to two thirds.
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spelling pubmed-78059402021-01-25 Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning Lee, Jun-Young Eom, Jaemin Yu, Sung Yol Cho, Kyujin Front Robot AI Robotics and AI Soft grippers with soft and flexible materials have been widely researched to improve the functionality of grasping. Although grippers that can grasp various objects with different shapes are important, a large number of industrial applications require a gripper that is targeted for a specified object. In this paper, we propose a design methodology for soft grippers that are customized to grasp single dedicated objects. A customized soft gripper can safely and efficiently grasp a dedicated target object with lowered surface contact forces while maintaining a higher lifting force, compared to its non-customized counterpart. A simplified analytical model and a fabrication method that can rapidly customize and fabricate soft grippers are proposed. Stiffness patterns were implemented onto the constraint layers of pneumatic bending actuators to establish actuated postures with irregular bending curvatures in the longitudinal direction. Soft grippers with customized stiffness patterns yielded higher shape conformability to target objects than non-patterned regular soft grippers. The simplified analytical model represents the pneumatically actuated soft finger as a summation of interactions between its air chambers. Geometric approximations and pseudo-rigid-body modeling theory were employed to build the analytical model. The customized soft grippers were compared with non-patterned soft grippers by measuring their lifting forces and contact forces while they grasped objects. Under the identical actuating pressure, the conformable grasping postures enabled customized soft grippers to have almost three times the lifting force than that of non-patterned soft grippers, while the maximum contact force was reduced to two thirds. Frontiers Media S.A. 2020-09-18 /pmc/articles/PMC7805940/ /pubmed/33501280 http://dx.doi.org/10.3389/frobt.2020.00114 Text en Copyright © 2020 Lee, Eom, Yu and Cho. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Lee, Jun-Young
Eom, Jaemin
Yu, Sung Yol
Cho, Kyujin
Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning
title Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning
title_full Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning
title_fullStr Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning
title_full_unstemmed Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning
title_short Customization Methodology for Conformable Grasping Posture of Soft Grippers by Stiffness Patterning
title_sort customization methodology for conformable grasping posture of soft grippers by stiffness patterning
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805940/
https://www.ncbi.nlm.nih.gov/pubmed/33501280
http://dx.doi.org/10.3389/frobt.2020.00114
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