Information-rich path planning under general constraints using Rapidly-exploring Random Trees
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/59684 |
| _version_ | 1826211384997707776 |
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| author | Levine, Daniel S., Ph. D. Massachusetts Institute of Technology. |
| author2 | Jonathan P. How. |
| author_facet | Jonathan P. How. Levine, Daniel S., Ph. D. Massachusetts Institute of Technology. |
| author_sort | Levine, Daniel S., Ph. D. Massachusetts Institute of Technology. |
| collection | MIT |
| description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010. |
| first_indexed | 2024-09-23T15:05:03Z |
| format | Thesis |
| id | mit-1721.1/59684 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T15:05:03Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/596842019-04-12T09:06:49Z Information-rich path planning under general constraints using Rapidly-exploring Random Trees Levine, Daniel S., Ph. D. Massachusetts Institute of Technology. Jonathan P. How. Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Aeronautics and Astronautics. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 99-104). This thesis introduces the Information-rich Rapidly-exploring Random Tree (IRRT), an extension of the RRT algorithm that embeds information collection as predicted using Fisher information matrices. The primary contribution of this trajectory generation algorithm is target-based information maximization in general (possibly heavily constrained) environments, with complex vehicle dynamic constraints and sensor limitations, including limited resolution and narrow field-of-view. Extensions of IRRT both for decentralized, multiagent missions and for information-rich planning with multimodal distributions are presented. IRRT is distinguished from previous solution strategies by its computational tractability and general constraint characterization. A progression of simulation results demonstrates that this implementation can generate complex target-tracking behaviors from a simple model of the trade-off between information gathering and goal arrival. by Daniel S. Levine. S.M. 2010-10-29T18:11:38Z 2010-10-29T18:11:38Z 2010 2010 Thesis http://hdl.handle.net/1721.1/59684 668232182 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 104 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Aeronautics and Astronautics. Levine, Daniel S., Ph. D. Massachusetts Institute of Technology. Information-rich path planning under general constraints using Rapidly-exploring Random Trees |
| title | Information-rich path planning under general constraints using Rapidly-exploring Random Trees |
| title_full | Information-rich path planning under general constraints using Rapidly-exploring Random Trees |
| title_fullStr | Information-rich path planning under general constraints using Rapidly-exploring Random Trees |
| title_full_unstemmed | Information-rich path planning under general constraints using Rapidly-exploring Random Trees |
| title_short | Information-rich path planning under general constraints using Rapidly-exploring Random Trees |
| title_sort | information rich path planning under general constraints using rapidly exploring random trees |
| topic | Aeronautics and Astronautics. |
| url | http://hdl.handle.net/1721.1/59684 |
| work_keys_str_mv | AT levinedanielsphdmassachusettsinstituteoftechnology informationrichpathplanningundergeneralconstraintsusingrapidlyexploringrandomtrees |