Published October 2013
| public
Journal Article
Feature Localization Using Kinematics and Impulsive Hybrid Optimization
- Creators
- Leong, Yoke Peng
- Murphey, Todd D.
Abstract
This paper focuses on detecting and localizing a surface feature on an otherwise uniform surface using kinematic data collected during an exploratory procedure. Assuming that characteristics of the feature shape and surface shape are known, a surface feature is detected by performing least squares estimation calculated via impulsive hybrid system optimization. The optimization routine is based on an adjoint formulation which allows the algorithm to be computationally efficient and scalable. This algorithm is also shown to perform well with the presence of measurement noise and model noise, both in simulations and experiments.
Additional Information
© 2013 IEEE. Manuscript received July 16, 2012; revised November 30, 2012; accepted February 17, 2013. Date of publication May 03, 2013; date of current version October 02, 2013. This paper was recommended for publication by Associate Editor W. Sheng and Editor A. Bicchi upon evaluation of the reviewers' comments. This work was supported by the National Science Foundation under Award IIS-1018167. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.Additional details
- Eprint ID
- 42347
- DOI
- 10.1109/TASE.2013.2259233
- Resolver ID
- CaltechAUTHORS:20131108-152945276
- IIS-1018167
- NSF
- Created
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2013-11-09Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field
- Other Numbering System Name
- INSPEC Accession Number
- Other Numbering System Identifier
- 13811280