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• W1570540164 abstract "We introduce a particle filter-based approach to representing and actively reducing uncertainty over articulated motion models. The presented method provides a probabilistic model that integrates visual observations with feedback from manipulation actions to best characterize a distribution of possible articulation models. We evaluate several action selection methods to efficiently reduce the uncertainty about the articulation model. The full system is experimentally evaluated using a PR2 mobile manipulator. Our experiments demonstrate that the proposed system allows for intelligent reasoning about sparse, noisy data in a number of common manipulation scenarios." @default.
• W1570540164 created "2016-06-24" @default.
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• W1570540164 date "2015-05-01" @default.
• W1570540164 modified "2023-09-30" @default.
• W1570540164 title "Active articulation model estimation through interactive perception" @default.
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• W1570540164 doi "https://doi.org/10.1109/icra.2015.7139655" @default.
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