This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. ; Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 ; Cataloged from student-submitted PDF version of thesis. ; Includes bibliographical references (pages 59-61). ; With autonomous vehicle development increasing, urban planners and designers are examining the impacts they will have on our everyday lives. As our technology becomes more powerful, roboticists are expanding their scope from roads and highways to canals and other waterways in order to develop Autonomous Surface Vehicles (ASVs). These ASVs can drastically change the way we move and live within a city. In addition to transportation, ASVs can be used as a new type of infrastructure that allows for smarter waste collection and also the creation of on demand dynamic infrastructure such as platforms and bridges by allowing them to create rigid connections between each other. This thesis presents algorithms for creating this infrastructure by proposing methods for planning and executing multi-Roboat shapeshifting sequences. Shapeshifting allows for a group of ASVs to autonomously self-reconfigure and is absolutely critical in order to realize the proposed use cases. The presented algorithms were developed for use on a fleet of heterogeneous robots, introducing novel research questions in the field of self-reconfiguring robots. ; by Ryan Henderson Kelly. ; M. Eng. ; M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science


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    Titel :

    Algorithms for planning and executing multi-roboat shapeshifting



    Erscheinungsdatum :

    2019-01-01


    Anmerkungen:

    1128024342


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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