File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Mutation analysis models for visual servoing in nanomanipulations

TitleMutation analysis models for visual servoing in nanomanipulations
Authors
Issue Date2011
Citation
Proceedings of the IEEE Conference on Decision and Control, 2011, p. 5683-5688 How to Cite?
AbstractThis paper has two purposes: investigating a featureless visual servoing approach based on mutation analysis and proposing a visual servo control method for nanomanipulations. For the first purpose, the featureless visual servoing method is needed because traditional visual servoing relies heavily on robust feature extraction and tracking, which are very difficult in natural environment. The mutation analysis based approach in this paper considers the image as a set, and designs a controller to make the distance between the initial and goal image sets converge to zero, thereby steering the initial image to the goal image. For the second purpose, atomic force microscopic (AFM) based nanomanipulations with subnanometer accuracy are very difficult because the position sensor cannot provide valuable feedback due to large noises at this precision level. We propose to use the images obtained by AFM and perform a visual servo control. This method, independent of external sensors, can directly perform control on the AFM end tip's position. The featureless controller is successfully validated on AFM images and the results suggest a potential precision enhancement for nanomanipulations. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/213235
ISSN

 

DC FieldValueLanguage
dc.contributor.authorZhao, Jianguo-
dc.contributor.authorSong, Bo-
dc.contributor.authorXi, Ning-
dc.contributor.authorWai, King-
dc.contributor.authorLai, Chiu-
dc.date.accessioned2015-07-28T04:06:37Z-
dc.date.available2015-07-28T04:06:37Z-
dc.date.issued2011-
dc.identifier.citationProceedings of the IEEE Conference on Decision and Control, 2011, p. 5683-5688-
dc.identifier.issn0191-2216-
dc.identifier.urihttp://hdl.handle.net/10722/213235-
dc.description.abstractThis paper has two purposes: investigating a featureless visual servoing approach based on mutation analysis and proposing a visual servo control method for nanomanipulations. For the first purpose, the featureless visual servoing method is needed because traditional visual servoing relies heavily on robust feature extraction and tracking, which are very difficult in natural environment. The mutation analysis based approach in this paper considers the image as a set, and designs a controller to make the distance between the initial and goal image sets converge to zero, thereby steering the initial image to the goal image. For the second purpose, atomic force microscopic (AFM) based nanomanipulations with subnanometer accuracy are very difficult because the position sensor cannot provide valuable feedback due to large noises at this precision level. We propose to use the images obtained by AFM and perform a visual servo control. This method, independent of external sensors, can directly perform control on the AFM end tip's position. The featureless controller is successfully validated on AFM images and the results suggest a potential precision enhancement for nanomanipulations. © 2011 IEEE.-
dc.languageeng-
dc.relation.ispartofProceedings of the IEEE Conference on Decision and Control-
dc.titleMutation analysis models for visual servoing in nanomanipulations-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/CDC.2011.6161488-
dc.identifier.scopuseid_2-s2.0-84860683777-
dc.identifier.spage5683-
dc.identifier.epage5688-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats