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111683 |
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|a Garrett, Caelan Reed
|e author
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
|e contributor
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|a Garrett, Caelan Reed
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|a Lozano-Perez, Tomas
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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 Backward-forward search for manipulation planning
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|b Institute of Electrical and Electronics Engineers (IEEE),
|c 2017-10-03T18:36:12Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/111683
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|a In this paper we address planning problems in high-dimensional hybrid configuration spaces, with a particular focus on manipulation planning problems involving many objects. We present the hybrid backward-forward (HBF) planning algorithm that uses a backward identification of constraints to direct the sampling of the infinite action space in a forward search from the initial state towards a goal configuration. The resulting planner is probabilistically complete and can effectively construct long manipulation plans requiring both prehensile and nonprehensile actions in cluttered environments.
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|a United States. Office of Naval Research (Grant N00014-14-1-0486)
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|a United States. Air Force Office of Scientific Research (Grant FA23861014135)
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|a United States. Army Research Office (Grant W911NF1410433)
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|a en_US
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|a Article
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|t 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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