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Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm

This paper describes a novel electrostatically actuated microgripper with freeform geometries designed by a genetic algorithm. This new semiautomated design methodology is capable of designing near-optimal MEMS devices that are robust to fabrication tolerances. The use of freeform geometries designe...

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Autores principales: Wang, Chen, Wang, Yuan, Fang, Weidong, Song, Xiaoxiao, Quan, Aojie, Gidts, Michiel, Zhang, Hemin, Liu, Huafeng, Bai, Jian, Sadeghpour, Sina, Kraft, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733005/
https://www.ncbi.nlm.nih.gov/pubmed/35047208
http://dx.doi.org/10.1038/s41378-021-00336-0
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author Wang, Chen
Wang, Yuan
Fang, Weidong
Song, Xiaoxiao
Quan, Aojie
Gidts, Michiel
Zhang, Hemin
Liu, Huafeng
Bai, Jian
Sadeghpour, Sina
Kraft, Michael
author_facet Wang, Chen
Wang, Yuan
Fang, Weidong
Song, Xiaoxiao
Quan, Aojie
Gidts, Michiel
Zhang, Hemin
Liu, Huafeng
Bai, Jian
Sadeghpour, Sina
Kraft, Michael
author_sort Wang, Chen
collection PubMed
description This paper describes a novel electrostatically actuated microgripper with freeform geometries designed by a genetic algorithm. This new semiautomated design methodology is capable of designing near-optimal MEMS devices that are robust to fabrication tolerances. The use of freeform geometries designed by a genetic algorithm significantly improves the performance of the microgripper. An experiment shows that the designed microgripper has a large displacement (91.5 μm) with a low actuation voltage (47.5 V), which agrees well with the theory. The microgripper has a large actuation displacement and can handle micro-objects with a size from 10 to 100 μm. A grasping experiment on human hair with a diameter of 77 μm was performed to prove the functionality of the gripper. The result confirmed the superior performance of the new design methodology enabling freeform geometries. This design method can also be extended to the design of many other MEMS devices.
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spelling pubmed-87330052022-01-18 Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm Wang, Chen Wang, Yuan Fang, Weidong Song, Xiaoxiao Quan, Aojie Gidts, Michiel Zhang, Hemin Liu, Huafeng Bai, Jian Sadeghpour, Sina Kraft, Michael Microsyst Nanoeng Article This paper describes a novel electrostatically actuated microgripper with freeform geometries designed by a genetic algorithm. This new semiautomated design methodology is capable of designing near-optimal MEMS devices that are robust to fabrication tolerances. The use of freeform geometries designed by a genetic algorithm significantly improves the performance of the microgripper. An experiment shows that the designed microgripper has a large displacement (91.5 μm) with a low actuation voltage (47.5 V), which agrees well with the theory. The microgripper has a large actuation displacement and can handle micro-objects with a size from 10 to 100 μm. A grasping experiment on human hair with a diameter of 77 μm was performed to prove the functionality of the gripper. The result confirmed the superior performance of the new design methodology enabling freeform geometries. This design method can also be extended to the design of many other MEMS devices. Nature Publishing Group UK 2022-01-06 /pmc/articles/PMC8733005/ /pubmed/35047208 http://dx.doi.org/10.1038/s41378-021-00336-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wang, Chen
Wang, Yuan
Fang, Weidong
Song, Xiaoxiao
Quan, Aojie
Gidts, Michiel
Zhang, Hemin
Liu, Huafeng
Bai, Jian
Sadeghpour, Sina
Kraft, Michael
Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm
title Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm
title_full Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm
title_fullStr Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm
title_full_unstemmed Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm
title_short Design of a large-range rotary microgripper with freeform geometries using a genetic algorithm
title_sort design of a large-range rotary microgripper with freeform geometries using a genetic algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733005/
https://www.ncbi.nlm.nih.gov/pubmed/35047208
http://dx.doi.org/10.1038/s41378-021-00336-0
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