Leong, Yoke Peng and Murphey, Todd D. (2013) Feature Localization Using Kinematics and Impulsive Hybrid Optimization. IEEE Transactions on Automation Science and Engineering, 10 (4). pp. 957-968. ISSN 1545-5955. http://resolver.caltech.edu/CaltechAUTHORS:20131108-152945276
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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.|
|Subject Keywords:||Feature detection; feature localization; hybrid optimal control; tactile estimation|
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|Official Citation:||Yoke Peng Leong; Murphey, T., "Feature Localization Using Kinematics and Impulsive Hybrid Optimization," Automation Science and Engineering, IEEE Transactions on , vol.10, no.4, pp.957,968, Oct. 2013 doi: 10.1109/TASE.2013.2259233|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Tony Diaz|
|Deposited On:||09 Nov 2013 00:10|
|Last Modified:||09 Nov 2013 00:10|
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