{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/117300"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/117300","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Establishing a relative positioning system to achieve mobile localization","abstract":"There are an increasing number of situations in which the location of some digital device is known, but the methods to communicate with it are unknown. These situations can frustrate users and lead to the non-adoption to new, beneficial technologies. To combat this, I propose a relative positioning system between digital devices in order for each device to learn the relative locations of nearby devices. I explore three separate methods of establishing this positioning system. The first uses ultrasonic range-finding to localize nearby devices. The second uses WiFi range finding between mobile devices and stationary WiFi access points. The final method uses machine vision to jointly localize two devices observing the same scene from different angle. Ultimately none of these methods were fully implemented, but an analysis is given for the advantages and disadvantages of using these methods.","abstract_html":"There are an increasing number of situations in which the location of some digital device is known, but the methods to communicate with it are unknown. These situations can frustrate users and lead to the non-adoption to new, beneficial technologies. To combat this, I propose a relative positioning system between digital devices in order for each device to learn the relative locations of nearby devices. I explore three separate methods of establishing this positioning system. The first uses ultrasonic range-finding to localize nearby devices. The second uses WiFi range finding between mobile devices and stationary WiFi access points. The final method uses machine vision to jointly localize two devices observing the same scene from different angle. Ultimately none of these methods were fully implemented, but an analysis is given for the advantages and disadvantages of using these methods.","abstract_has_math":false,"creators":["Copeland, Brian W"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Chris Schmandt."],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-22T22:21:09Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses are protected by copyright. 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The certified thesis is available in the Institute Archives and Special Collections.","\"June 2017.\" Cataloged from student-submitted PDF version of thesis.","Includes bibliographical references (pages 67-69)."]},{"key":"dc:description.abstract","label":"Abstract","values":["There are an increasing number of situations in which the location of some digital device is known, but the methods to communicate with it are unknown. These situations can frustrate users and lead to the non-adoption to new, beneficial technologies. To combat this, I propose a relative positioning system between digital devices in order for each device to learn the relative locations of nearby devices. I explore three separate methods of establishing this positioning system. The first uses ultrasonic range-finding to localize nearby devices. The second uses WiFi range finding between mobile devices and stationary WiFi access points. The final method uses machine vision to jointly localize two devices observing the same scene from different angle. Ultimately none of these methods were fully implemented, but an analysis is given for the advantages and disadvantages of using these methods."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M. Eng."]},{"key":"dc:title","label":"Title","values":["Establishing a relative positioning system to achieve mobile localization"]}]}],"canonical_facts":{"dc:contributor.advisor":["Chris Schmandt."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:creator":["Copeland, Brian W"],"dc:date.accessioned":["2018-08-08T18:52:50Z"],"dc:date.available":["2018-08-08T18:52:50Z"],"dc:date.issued":["2017"],"dc:description":["Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","\"June 2017.\" Cataloged from student-submitted PDF version of thesis.","Includes bibliographical references (pages 67-69)."],"dc:description.abstract":["There are an increasing number of situations in which the location of some digital device is known, but the methods to communicate with it are unknown. These situations can frustrate users and lead to the non-adoption to new, beneficial technologies. To combat this, I propose a relative positioning system between digital devices in order for each device to learn the relative locations of nearby devices. I explore three separate methods of establishing this positioning system. The first uses ultrasonic range-finding to localize nearby devices. 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