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Sensor Planning for Object Pose Estimation and Identification

Ma, Jeremy and Burdick, Joel (2009) Sensor Planning for Object Pose Estimation and Identification. In: ROSE proceedings : 2009 IEEE International Workshop on Robotic and Sensors Environments. IEEE , Piscataway, NJ, pp. 69-74. ISBN 978-1-4244-4777-0.

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This paper proposes a novel approach to sensor planning for simultaneous object identification and 3D pose estimation. We consider the problem of determining the next-best-view for a movable sensor (or an autonomous agent) to identify an unknown object from among a database of known object models. We use an information theoretic approach to define a metric (based on the difference between the current and expected model entropy) that guides the selection of the optimal control action. We present a generalized algorithm that can be used in sensor planning for object identification and pose estimation. Experimental results are also presented to validate the proposed algorithm.

Item Type:Book Section
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Additional Information:© 2009 IEEE. Issue Date: 6-7 Nov. 2009. Date of Current Version: 18 December 2009.
Record Number:CaltechAUTHORS:20110524-074302858
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Official Citation:Ma, J.; Burdick, J.; , "Sensor planning for object pose estimation and identification," Robotic and Sensors Environments, 2009. ROSE 2009. IEEE International Workshop on , vol., no., pp.69-74, 6-7 Nov. 2009 doi: 10.1109/ROSE.2009.5355995 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:23769
Deposited By: Ruth Sustaita
Deposited On:24 May 2011 15:42
Last Modified:03 Oct 2019 02:49

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