dc.contributor.advisor | Nicholas Roy. | en_US |
dc.contributor.author | Park, Sooho, S.M. Massachusetts Institute of Technology | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. | en_US |
dc.date.accessioned | 2009-06-30T16:32:43Z | |
dc.date.available | 2009-06-30T16:32:43Z | |
dc.date.copyright | 2008 | en_US |
dc.date.issued | 2008 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/45887 | |
dc.description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. | en_US |
dc.description | Includes bibliographical references (p. 104-108). | en_US |
dc.description.abstract | Through the combined use of regression techniques, we will learn models of the uncertainty propagation efficiently and accurately to replace computationally intensive Monte- Carlo simulations in informative path planning. This will enable us to decrease the uncertainty of the weather estimates more than current methods by enabling the evaluation of many more candidate paths given the same amount of resources. The learning method and the path planning method will be validated by the numerical experiments using the Lorenz-2003 model [32], an idealized weather model. | en_US |
dc.description.statementofresponsibility | by Sooho Park. | en_US |
dc.format.extent | 108 p. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | 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. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Electrical Engineering and Computer Science. | en_US |
dc.title | Learning for informative path planning | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
dc.identifier.oclc | 320436167 | en_US |