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dc.contributor.advisorJohn N. Tsitsiklis.en_US
dc.contributor.authorHickman, Randal Een_US
dc.date.accessioned2006-03-29T18:35:41Z
dc.date.available2006-03-29T18:35:41Z
dc.date.copyright2005en_US
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/32340
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2005.en_US
dc.descriptionIncludes bibliographical references (p. 144-146).en_US
dc.description.abstractAutonomous vehicles often operate in environments with imperfect information. This thesis addresses the case of a system of autonomous vehicles and sensors attempting to intercept a moving object of interest that arrives stochastically and moves stochastically after arrival. A sensor array is placed in the area of expected arrivals. As the object of interest moves across the sensor system, the system initially receives perfect information of the object's movements. After the object of interest leaves the sensor system, the algorithm uses statistical estimation techniques to develop confidence intervals about points of expected interception. The algorithm assigns the optimal, autonomous chase vehicle from a set of pre-positioned autonomous vehicles, develops movement commands for the assigned vehicle, and considers reassignment of chase vehicles as appropriate given the stochastic movements of the object of interest. Dynamic programming is employed to optimize system parameters, and the thesis considers a reformulation of the problem that uses dynamic programming as a structural model for the entire algorithm.en_US
dc.description.statementofresponsibilityby Randal E. Hickman.en_US
dc.format.extent146 p.en_US
dc.format.extent8115890 bytes
dc.format.extent8123533 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectOperations Research Center.en_US
dc.titleInterception algorithm for autonomous vehicles with imperfect informationen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
dc.contributor.departmentSloan School of Management
dc.identifier.oclc61463356en_US


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