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dc.contributor.advisorAgah, Arvin
dc.contributor.authorJohnson, David O.
dc.date.accessioned2009-02-02T06:10:33Z
dc.date.available2009-02-02T06:10:33Z
dc.date.issued2008-01-01
dc.date.submitted2009
dc.identifier.otherhttp://dissertations.umi.com/ku:10011
dc.identifier.urihttp://hdl.handle.net/1808/4347
dc.description.abstractThe hypothesis for this research is that applying the Human Computer Interaction (HCI) concepts of using multiple modalities, dialog management, context, and semantics to Human Robot Interaction (HRI) will improve the performance of Instruction Based Learning (IBL) compared to only using speech. We tested the hypothesis by simulating a domestic robot that can be taught to clean a house using a multi-modal interface. We used a method of semantically integrating the inputs from multiple modalities and contexts that multiplies a confidence score for each input by a Fusion Weight, sums the products, and then uses the input with the highest product sum. We developed an algorithm for determining the Fusion Weights. We concluded that different modalities, contexts, and modes of dialog management impact human robot interaction; however, which combination is better depends on the importance of the accuracy of learning what is taught versus the succinctness of the dialog between the user and the robot.
dc.format.extent265 pages
dc.language.isoEN
dc.publisherUniversity of Kansas
dc.rightsThis item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
dc.subjectArtificial intelligence
dc.subjectEngineering
dc.subjectRobotics
dc.subjectComputer science
dc.subjectHuman robot interaction
dc.subjectInstruction based learning
dc.subjectMultiple modalities
dc.subjectRobot learning
dc.subjectSemantic integration
dc.titleHUMAN ROBOT INTERACTION THROUGH SEMANTIC INTEGRATION OF MULTIPLE MODALITIES, DIALOG MANAGEMENT, AND CONTEXTS
dc.typeDissertation
dc.contributor.cmtememberChakrabarti, Swapan
dc.contributor.cmtememberChen, Xue-wen
dc.contributor.cmtememberPotetz, Brian
dc.contributor.cmtememberWilson, Sara
dc.thesis.degreeDisciplineElectrical Engineering & Computer Science
dc.thesis.degreeLevelPh.D.
kusw.oastatusna
kusw.oapolicyThis item does not meet KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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