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Franz Hover. Englot, Brendan J Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering 2010-05-25T19:23:19Z 2010-05-25T19:23:19Z 2009 2009 http://hdl.handle.net/1721.1/54880 613211731 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student submitted PDF version of thesis. Includes bibliographical references (p. 114-118). The aim of this analysis is to explore the fundamental stability issues of a robotic vehicle carrying out localization, mapping, and feedback control in a perturbation-filled environment. Motivated by the application of an ocean vehicle performing an autonomous ship hull inspection, a planar vehicle model performs localization using point features from a given map. Cases in which the agent must update the map are also considered. The stability of the marine robot controller and estimator duo is investigated using a pair of theorems requiring boundedness and convergence of the transition matrix Euclidean norm. These theorems yield a stability test for the feedback controller. Perturbations are then considered using a theorem on the convergence on the perturbed system transition matrix, yielding a robustness test for the estimator. Together, these tests form a set of tools which can be used in planning and evaluating the robustness of marine vehicle survey trajectories, which is demonstrated through experiment. An augmented A* kinodynamic path-planning algorithm is then implemented to search the control input space for the globally robustness-optimal survey trajectory. by Brendan J. Englot. S.M. 118 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 Mechanical Engineering. Stability and robustness analysis tools for marine robot localization and mapping applications Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="90df2d36-2c11-4378-b3b9-1e6a318b8c47"> <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>Stability and robustness analysis tools for marine robot localization and mapping applications</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2009</PublicationDate> <Authors> <Author> <DisplayName>Englot, Brendan J</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>Mechanical Engineering.</Keyword> <Abstract>The aim of this analysis is to explore the fundamental stability issues of a robotic vehicle carrying out localization, mapping, and feedback control in a perturbation-filled environment. Motivated by the application of an ocean vehicle performing an autonomous ship hull inspection, a planar vehicle model performs localization using point features from a given map. Cases in which the agent must update the map are also considered. The stability of the marine robot controller and estimator duo is investigated using a pair of theorems requiring boundedness and convergence of the transition matrix Euclidean norm. These theorems yield a stability test for the feedback controller. Perturbations are then considered using a theorem on the convergence on the perturbed system transition matrix, yielding a robustness test for the estimator. Together, these tests form a set of tools which can be used in planning and evaluating the robustness of marine vehicle survey trajectories, which is demonstrated through experiment. An augmented A* kinodynamic path-planning algorithm is then implemented to search the control input space for the globally robustness-optimal survey trajectory.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>