Please use this identifier to cite or link to this item: https://doi.org/10.3390/mi6121461
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dc.titleCalibration of nanopositioning stages
dc.contributor.authorTan, N
dc.contributor.authorClévy, C
dc.contributor.authorChaillet, N
dc.date.accessioned2020-10-26T08:32:04Z
dc.date.available2020-10-26T08:32:04Z
dc.date.issued2015
dc.identifier.citationTan, N, Clévy, C, Chaillet, N (2015). Calibration of nanopositioning stages. Micromachines 6 (12) : 1856-1875. ScholarBank@NUS Repository. https://doi.org/10.3390/mi6121461
dc.identifier.issn2072666X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/180359
dc.description.abstractAccuracy is one of the most important criteria for the performance evaluation of microand nanorobots or systems. Nanopositioning stages are used to achieve the high positioning resolution and accuracy for a wide and growing scope of applications. However, their positioning accuracy and repeatability are not well known and difficult to guarantee, which induces many drawbacks for many applications. For example, in the mechanical characterisation of biological samples, it is difficult to perform several cycles in a repeatable way so as not to induce negative influences on the study. It also prevents one from controlling accurately a tool with respect to a sample without adding additional sensors for closed loop control. This paper aims at quantifying the positioning repeatability and accuracy based on the ISO 9283:1998 standard, and analyzing factors influencing positioning accuracy onto a case study of 1-DoF (Degree-of-Freedom) nanopositioning stage. The influence of thermal drift is notably quantified. Performances improvement of the nanopositioning stage are then investigated through robot calibration (i.e., open-loop approach). Two models (static and adaptive models) are proposed to compensate for both geometric errors and thermal drift. Validation experiments are conducted over a long period (several days) showing that the accuracy of the stage is improved from typical micrometer range to 400 nm using the static model and even down to 100 nm using the adaptive model. In addition, we extend the 1-DoF calibration to multi-DoF with a case study of a 2-DoF nanopositioning robot. Results demonstrate that the model efficiently improved the 2D accuracy from 1400 nm to 200 nm. © 2015 by the authors.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20201031
dc.subjectDegrees of freedom (mechanics)
dc.subjectError compensation
dc.subjectAccuracy
dc.subjectGeometric errors
dc.subjectNano-positioning stages
dc.subjectOpen-loop
dc.subjectRepeatability
dc.subjectThermal compensation
dc.subjectCalibration
dc.typeArticle
dc.contributor.departmentBIOMEDICAL ENGINEERING
dc.description.doi10.3390/mi6121461
dc.description.sourcetitleMicromachines
dc.description.volume6
dc.description.issue12
dc.description.page1856-1875
dc.published.statePublished
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