Inferring beliefs for search and rescue from natural language
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2019
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| Online Access: | http://hdl.handle.net/1721.1/120439 |
| _version_ | 1826217243742044160 |
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| author | Schurr, Naomi D. (Naomi Danika) |
| author2 | Nicholas Roy. |
| author_facet | Nicholas Roy. Schurr, Naomi D. (Naomi Danika) |
| author_sort | Schurr, Naomi D. (Naomi Danika) |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018. |
| first_indexed | 2024-09-23T17:00:16Z |
| format | Thesis |
| id | mit-1721.1/120439 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T17:00:16Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1204392019-04-11T05:19:45Z Inferring beliefs for search and rescue from natural language Schurr, Naomi D. (Naomi Danika) Nicholas Roy. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Aeronautics and Astronautics. Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 97-101). A learned natural language robotic interface can allow a human operator to intuitively communicate instructions to a robot. A number of models, including probabilistic grounding graphs, have been used to ground natural language input to the real-world tasks a robot must perform. In this thesis, I provide two extensions to existing work in grounding natural language instructions. First, I apply an existing probabilistic grounding graph model in the context of outdoor search and rescue, introducing a new set of groundings to allow a continuous cost map to be inferred from the natural language. Second, I incorporate pool-based active learning into the training of the probabilistic grounding graph model, which shows promise for reducing the number of labeled examples needed to train the model. by Naomi D. Schurr. S.M. 2019-02-14T15:51:43Z 2019-02-14T15:51:43Z 2018 2018 Thesis http://hdl.handle.net/1721.1/120439 1084654173 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 101 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Aeronautics and Astronautics. Schurr, Naomi D. (Naomi Danika) Inferring beliefs for search and rescue from natural language |
| title | Inferring beliefs for search and rescue from natural language |
| title_full | Inferring beliefs for search and rescue from natural language |
| title_fullStr | Inferring beliefs for search and rescue from natural language |
| title_full_unstemmed | Inferring beliefs for search and rescue from natural language |
| title_short | Inferring beliefs for search and rescue from natural language |
| title_sort | inferring beliefs for search and rescue from natural language |
| topic | Aeronautics and Astronautics. |
| url | http://hdl.handle.net/1721.1/120439 |
| work_keys_str_mv | AT schurrnaomidnaomidanika inferringbeliefsforsearchandrescuefromnaturallanguage |