Multi-DoF Optothermal Microgripper for Micromanipulation Applications

IF 4.6 2区 计算机科学 Q2 ROBOTICS
Kaiwen Chen;Alex J. Thompson;Belal Ahmad
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引用次数: 0

Abstract

Microgrippers have emerged in minimally invasive surgery and biomedical applications, enabling tasks such as gripping, micro-assembly, and cell manipulation. Realizing microgrippers with multiple degrees-of-freedom (DoFs) enables higher dexterity and multi-functionality. However, due to their small size and limited working space, the development of microgrippers with multi-DoF faces great challenges, requiring complex fabrication technologies and actuation mechanisms. Here we report a novel optothermally-actuated multi-DoF microgripper with multiple functionalities for micromanipulation. For this, three types of optothermal microactuators, namely bimaterial microjoints, chevron-shaped microactuators, and hot-cold arm microactuators are considered. The suitability of the chevron-shaped and hot-cold arm microactuators for mechanical pushing tasks is evaluated through modeling and simulation. Then, a 3-DoF microgripper incorporating two spiral bimaterial microjoints and one chevron-shaped microactuator is designed and fabricated. The selective and individual actuation of these microactuators is facilitated using a fiber bundle and a digital micromirror device. Finally, the performance and multi-functionality of the microgripper are demonstrated by performing multiple micromanipulation tasks of mechanical pushing and pick-and-release of microbeads. This work provides a proof of concept of an optothermal multi-DoF microgripper with multiple functionalities, opening the way for advanced dexterity at the microscale that is difficult to achieve using the current technology.
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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