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An augmented steady hand system for ...
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Kumar, Rajesh.
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An augmented steady hand system for precise micromanipulation.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
An augmented steady hand system for precise micromanipulation./
作者:
Kumar, Rajesh.
面頁冊數:
109 p.
附註:
Adviser: Russell H. Taylor.
Contained By:
Dissertation Abstracts International62-02B.
標題:
Computer Science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3006288
ISBN:
9780493155838
An augmented steady hand system for precise micromanipulation.
Kumar, Rajesh.
An augmented steady hand system for precise micromanipulation.
- 109 p.
Adviser: Russell H. Taylor.
Thesis (Ph.D.)--The Johns Hopkins University, 2001.
Steady Hand cooperative manipulation is a hands-on approach that integrates seamlessly in the surgical practice. In steady hand manipulation, the tool is held simultaneously by the user and the robot and the robot complies to forces applied by the user. Steady hand manipulation promises significant improvements in safety, accuracy over conventional practice at minimal cost and training to the user. It also offers a way around the difficult problem of encoding human intelligence, and preserves the benefits from experience and training.
ISBN: 9780493155838Subjects--Topical Terms:
626642
Computer Science.
An augmented steady hand system for precise micromanipulation.
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Steady Hand cooperative manipulation is a hands-on approach that integrates seamlessly in the surgical practice. In steady hand manipulation, the tool is held simultaneously by the user and the robot and the robot complies to forces applied by the user. Steady hand manipulation promises significant improvements in safety, accuracy over conventional practice at minimal cost and training to the user. It also offers a way around the difficult problem of encoding human intelligence, and preserves the benefits from experience and training.
520
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We explore the possibility of encoding/utilizing task descriptions to improve transparency and performance of a steady hand manipulation task. This is done by constructing state space representations of the task. The user's interaction with the robot, tool-tissue interactions, and other sensory and planning inputs can be used to identify the task state and modify the behavior of the robot by using optimized task and control parameters. Validation experiments for several cooperative tasks with and without augmentation are presented.
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