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Emilio Frazzoli. Panish, Robert Martin Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics 2009-08-25T17:59:58Z 2009-08-25T17:59:58Z 2008 2008 http://hdl.handle.net/1721.1/46370 422549622 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Includes bibliographical references (p. 107-108). A vision based navigation alter is developed for application on UAVs and tested in simulation. This alter is meant to allow the UAV to navigate in GPS-denied environments using measurements from a suite of cameras. The extended Kalman alter integrates measurements from multiple non-overlapping cameras as well as an IMU and occasional GPS. Simulations are conducted to evaluate the performance of the alter in a variety of fight regimes as well as to assess the value of using multiple cameras. Simulations demonstrate the value of using multiple cameras for egomotion estimation. Multiple non-overlapping cameras are useful for resolving motion in an unobservable direction that manifests as an ambiguity between translation and rotation. Additionally, multiple cameras are extremely useful when flying in an environment such as an urban canyon, where features remain in the fields of view for a very short period of time. by Robert Martin Panish. S.M. 108 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. Vehicle egomotion estimation using computer vision Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="92fc031a-83cb-4091-ac77-1013763f6e1b"> <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>Vehicle egomotion estimation using computer vision</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2008</PublicationDate> <Authors> <Author> <DisplayName>Panish, Robert Martin</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>A vision based navigation alter is developed for application on UAVs and tested in simulation. This alter is meant to allow the UAV to navigate in GPS-denied environments using measurements from a suite of cameras. The extended Kalman alter integrates measurements from multiple non-overlapping cameras as well as an IMU and occasional GPS. Simulations are conducted to evaluate the performance of the alter in a variety of fight regimes as well as to assess the value of using multiple cameras. Simulations demonstrate the value of using multiple cameras for egomotion estimation. Multiple non-overlapping cameras are useful for resolving motion in an unobservable direction that manifests as an ambiguity between translation and rotation. Additionally, multiple cameras are extremely useful when flying in an environment such as an urban canyon, where features remain in the fields of view for a very short period of time.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>