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|a Lozano-Perez, Tomas
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Kaelbling, Leslie P.
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|a Lozano-Perez, Tomas
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|a Kaelbling, Leslie P.
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|a Unifying perception, estimation and action for mobile manipulation via belief space planning
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|b Institute of Electrical and Electronics Engineers (IEEE),
|c 2014-09-22T18:43:31Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/90270
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|a In this paper, we describe an integrated strategy for planning, perception, state-estimation and action in complex mobile manipulation domains. The strategy is based on planning in the belief space of probability distribution over states. Our planning approach is based on hierarchical symbolic regression (pre-image back-chaining). We develop a vocabulary of fluents that describe sets of belief states, which are goals and subgoals in the planning process. We show that a relatively small set of symbolic operators lead to task-oriented perception in support of the manipulation goals.
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|a National Science Foundation (U.S.) (Grant 019868)
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|a United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N00014-09-1-1051)
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|a United States. Air Force Office of Scientific Research (Grant AOARD-104135)
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|a en_US
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|a Article
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|t Proceedings of the 2012 IEEE International Conference on Robotics and Automation
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