Integrated robot task and motion planning in belief space
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 goal regressio...
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2012
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| Online Access: | http://hdl.handle.net/1721.1/71529 |
| _version_ | 1826198232207720448 |
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| author | Kaelbling, Leslie Pack Lozano-Perez, Tomas |
| author2 | Leslie Kaelbling |
| author_facet | Leslie Kaelbling Kaelbling, Leslie Pack Lozano-Perez, Tomas |
| author_sort | Kaelbling, Leslie Pack |
| collection | MIT |
| description | 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 goal 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. An implementation of this method is demonstrated in simulation and on a real PR2 robot, showing robust, flexible solution of mobile manipulation problems with multiple objects and substantial uncertainty. |
| first_indexed | 2024-09-23T11:01:49Z |
| id | mit-1721.1/71529 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:01:49Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | mit-1721.1/715292019-04-10T23:00:06Z Integrated robot task and motion planning in belief space Kaelbling, Leslie Pack Lozano-Perez, Tomas Leslie Kaelbling Tomas Lozano-Perez Learning and Intelligent Systems 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 goal 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. An implementation of this method is demonstrated in simulation and on a real PR2 robot, showing robust, flexible solution of mobile manipulation problems with multiple objects and substantial uncertainty. This work was supported in part by the NSF under Grant No. 1117325. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We also gratefully acknowledge support from ONR MURI grant N00014-09-1-1051, from AFOSR grant AOARD-104135 and from the Singapore Ministry of Education under a grant to the Singapore-MIT International Design Center. We thank Willow Garage for the use of the PR2 robot as part of the PR2 Beta Program. 2012-07-03T18:00:04Z 2012-07-03T18:00:04Z 2012-07-03 http://hdl.handle.net/1721.1/71529 MIT-CSAIL-TR-2012-019 Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported http://creativecommons.org/licenses/by-nc-nd/3.0/ 80 p. application/pdf |
| spellingShingle | Kaelbling, Leslie Pack Lozano-Perez, Tomas Integrated robot task and motion planning in belief space |
| title | Integrated robot task and motion planning in belief space |
| title_full | Integrated robot task and motion planning in belief space |
| title_fullStr | Integrated robot task and motion planning in belief space |
| title_full_unstemmed | Integrated robot task and motion planning in belief space |
| title_short | Integrated robot task and motion planning in belief space |
| title_sort | integrated robot task and motion planning in belief space |
| url | http://hdl.handle.net/1721.1/71529 |
| work_keys_str_mv | AT kaelblinglesliepack integratedrobottaskandmotionplanninginbeliefspace AT lozanopereztomas integratedrobottaskandmotionplanninginbeliefspace |