Sensor Planning For Object Pose Estimation And Identification
2009 IEEE INTERNATIONAL WORKSHOP ON ROBOTIC AND SENSORS ENVIRONMENTS (ROSE 2009)(2009)
摘要
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.
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关键词
information theory,object model,path planning,mobile robots,object recognition,robots,databases,entropy,autonomous agent,pose estimation,estimation,face,generic algorithm,planning,optimal control,3d pose estimation
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