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

Chen Wang, Yuan Wang, Weidong Fang, Xiaoxiao Song, Aojie Quan, Michiel Gidts, Hemin Zhang, Huafeng Liu, Jian Bai, Sina Sadeghpour, Michael Kraft

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

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.

Original languageEnglish
Article number3
JournalMicrosystems and Nanoengineering
Volume8
Issue number1
DOIs
StatePublished - Dec 2022
Externally publishedYes

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