Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation

The interactive nanomanipulation platform is established based on fuzzy control and connected region marking (CRM) algorithm in SEM. The 3D virtual nanomanipulation model is developed to make up the insufficiency of the 2D SEM image information, which provides the operator with depth and real-time v...

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Main Authors: Dongjie Li, Weibin Rong, Lining Sun, Bo You, Yu Zou, Wanzhe Xiao
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2012/803912
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spelling doaj-0af699a0dddf4aecb380c25de6aa9e122020-11-25T01:03:41ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/803912803912Fuzzy Control and Connected Region Marking Algorithm-Based SEM NanomanipulationDongjie Li0Weibin Rong1Lining Sun2Bo You3Yu Zou4Wanzhe Xiao5State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaState Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, ChinaThe interactive nanomanipulation platform is established based on fuzzy control and connected region marking (CRM) algorithm in SEM. The 3D virtual nanomanipulation model is developed to make up the insufficiency of the 2D SEM image information, which provides the operator with depth and real-time visual feedback information to guide the manipulation. The haptic device Omega3 is used as the master to control the 3D motion of the nanopositioner in master-slave mode and offer the force sensing to the operator controlled with fuzzy control algorithm. Aiming at sensing of force feedback during the nanomanipulation, the collision detection method of the virtual nanomanipulation model and the force rending model are studied to realize the force feedback of nanomanipulation. The CRM algorithm is introduced to process the SEM image which provides effective position data of the objects for updating the virtual environment (VE), and relevant issues such as calibration and update rate of VE are also discussed. Finally, the performance of the platform is validated by the ZnO nanowire manipulation experiments.http://dx.doi.org/10.1155/2012/803912
collection DOAJ
language English
format Article
sources DOAJ
author Dongjie Li
Weibin Rong
Lining Sun
Bo You
Yu Zou
Wanzhe Xiao
spellingShingle Dongjie Li
Weibin Rong
Lining Sun
Bo You
Yu Zou
Wanzhe Xiao
Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation
Mathematical Problems in Engineering
author_facet Dongjie Li
Weibin Rong
Lining Sun
Bo You
Yu Zou
Wanzhe Xiao
author_sort Dongjie Li
title Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation
title_short Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation
title_full Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation
title_fullStr Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation
title_full_unstemmed Fuzzy Control and Connected Region Marking Algorithm-Based SEM Nanomanipulation
title_sort fuzzy control and connected region marking algorithm-based sem nanomanipulation
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2012-01-01
description The interactive nanomanipulation platform is established based on fuzzy control and connected region marking (CRM) algorithm in SEM. The 3D virtual nanomanipulation model is developed to make up the insufficiency of the 2D SEM image information, which provides the operator with depth and real-time visual feedback information to guide the manipulation. The haptic device Omega3 is used as the master to control the 3D motion of the nanopositioner in master-slave mode and offer the force sensing to the operator controlled with fuzzy control algorithm. Aiming at sensing of force feedback during the nanomanipulation, the collision detection method of the virtual nanomanipulation model and the force rending model are studied to realize the force feedback of nanomanipulation. The CRM algorithm is introduced to process the SEM image which provides effective position data of the objects for updating the virtual environment (VE), and relevant issues such as calibration and update rate of VE are also discussed. Finally, the performance of the platform is validated by the ZnO nanowire manipulation experiments.
url http://dx.doi.org/10.1155/2012/803912
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