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Jonathan P. How. Toksoz, Tuna Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics 2013-02-15T14:40:26Z 2013-02-15T14:40:26Z 2012 2012 http://hdl.handle.net/1721.1/77117 825075196 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012. Cataloged from department-submitted PDF version of thesis. This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections. Includes bibliographical references (p. 95-99). This thesis describes the design and the implementation of the hardware platform for automated battery management with battery changing/charging capability for autonomous UAV missions with persistency requirement that extends the mission duration beyond the life of a single UAV battery. The platform is tested through a series of missions lasting at least 3 hours to prove it meets design requirements and to show its feasibility. This thesis also provides a method to modify existing scenarios to proactively plan for the battery maintenance so that the overall system performance is increased. The modifications made to the problem definition increased the state-space significantly, and means of solving a problem of that scale needed to be developed. To address this challenge, this thesis extends a previously developed approach called Incremental Feature Dependency Discovery (iFDD) by allowing to use caches from computer science literature to make conversion from basic features to extended features faster. By doing so, this method significantly reduces the computational complexity. by Tuna Toksoz. S.M. 99 p. eng Massachusetts Institute of Technology 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 Aeronautics and Astronautics. Design and implementation of an automated battery management platform Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="337db90d-0440-4661-adf5-2974ecf01abc"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Design and implementation of an automated battery management platform</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <Authors> <Author> <DisplayName>Toksoz, Tuna</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Aeronautics and Astronautics.</Keyword> <Abstract>This thesis describes the design and the implementation of the hardware platform for automated battery management with battery changing/charging capability for autonomous UAV missions with persistency requirement that extends the mission duration beyond the life of a single UAV battery. The platform is tested through a series of missions lasting at least 3 hours to prove it meets design requirements and to show its feasibility. This thesis also provides a method to modify existing scenarios to proactively plan for the battery maintenance so that the overall system performance is increased. The modifications made to the problem definition increased the state-space significantly, and means of solving a problem of that scale needed to be developed. To address this challenge, this thesis extends a previously developed approach called Incremental Feature Dependency Discovery (iFDD) by allowing to use caches from computer science literature to make conversion from basic features to extended features faster. By doing so, this method significantly reduces the computational complexity.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>