Sensor Planning for Object Pose Estimation and Identification
- Creators
- Ma, Jeremy
- Burdick, Joel
Abstract
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.
Additional Information
© 2009 IEEE. Issue Date: 6-7 Nov. 2009. Date of Current Version: 18 December 2009.Attached Files
Published - Ma2009p138702009_Ieee_International_Workshop_On_Robotic_And_Sensors_Environments__Rose_2009_.pdf
Files
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Additional details
- Eprint ID
- 23769
- Resolver ID
- CaltechAUTHORS:20110524-074302858
- Created
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2011-05-24Created from EPrint's datestamp field
- Updated
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2021-11-09Created from EPrint's last_modified field