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Stochastic Dynamics Modeling and Mot...
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ProQuest Information and Learning Co.
Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres./
作者:
Rajasekaran, Keshav.
面頁冊數:
1 online resource (45 pages)
附註:
Source: Masters Abstracts International, Volume: 57-02.
Contained By:
Masters Abstracts International57-02(E).
標題:
Mechanical engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9780355357301
Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres.
Rajasekaran, Keshav.
Stochastic Dynamics Modeling and Motion Control of Optically Trapped Microspheres.
- 1 online resource (45 pages)
Source: Masters Abstracts International, Volume: 57-02.
Thesis (Master's)
Includes bibliographical references
Automation of an optical tweezers system is critical to fully leverage its immense multiplexing capabilities, which allows for highly precise and reliable manipulation of microscopic dielectric objects. Although there has been substantial work in this context, automation has been limited to only transporting a few objects at a time, particularly while ensuring collision avoidances with other freely diffusing objects in the workspace. In this paper, we provide the first step in addressing this limitation by developing a new algorithm that combines a model predictive controller with a fast grid search-based path planning method. We validate the usefulness of the presented method through experiments with silica beads in water.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355357301Subjects--Topical Terms:
557493
Mechanical engineering.
Index Terms--Genre/Form:
554714
Electronic books.
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Automation of an optical tweezers system is critical to fully leverage its immense multiplexing capabilities, which allows for highly precise and reliable manipulation of microscopic dielectric objects. Although there has been substantial work in this context, automation has been limited to only transporting a few objects at a time, particularly while ensuring collision avoidances with other freely diffusing objects in the workspace. In this paper, we provide the first step in addressing this limitation by developing a new algorithm that combines a model predictive controller with a fast grid search-based path planning method. We validate the usefulness of the presented method through experiments with silica beads in water.
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