{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/35081"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/35081","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Decision algorithms for Unmanned Underwater Vehicles during offensive operations","abstract":"The field of research involving autonomous vehicles has expanded greatly over the past decade. This thesis addresses the case of a system of Unmanned Underwater Vehicles (UUVs) operating in littoral areas in an offensive capacity. A series of complementary algorithms were designed to collect information about an enemy vessell, and subsequently use this information to both select and move to a prefered intercept location that maximizes the opportunity to both re-acquire and destroy an enemy vessel. Additionally, within the context of a specifically designed simulation, key parameter changes were analyzed to determine their effectiveness to improve the system's performance as measured by four measures of effectiveness. A methodology was also designed to optimize the location of the engaging UUVs to maximize their effectiveness, and capitalize on the enemy movement within the operational area. Results are presented for both original locations and optimized locations, and initial findings provide insight into the effectiveness of the designed algorithms and statistical inference of these key parameter changes.","abstract_html":"The field of research involving autonomous vehicles has expanded greatly over the past decade. This thesis addresses the case of a system of Unmanned Underwater Vehicles (UUVs) operating in littoral areas in an offensive capacity. A series of complementary algorithms were designed to collect information about an enemy vessell, and subsequently use this information to both select and move to a prefered intercept location that maximizes the opportunity to both re-acquire and destroy an enemy vessel. Additionally, within the context of a specifically designed simulation, key parameter changes were analyzed to determine their effectiveness to improve the system's performance as measured by four measures of effectiveness. A methodology was also designed to optimize the location of the engaging UUVs to maximize their effectiveness, and capitalize on the enemy movement within the operational area. Results are presented for both original locations and optimized locations, and initial findings provide insight into the effectiveness of the designed algorithms and statistical inference of these key parameter changes.","abstract_has_math":false,"creators":["Smith, Tyler B. (Tyler Bradford)"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Civil and Environmental Engineering","school":null,"contributors":[],"advisors":["Margaret F. Nervegna and Cynthia Barnhart."],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006","date_published":"2006","updated_at":"2026-07-22T22:20:46Z","subjects":["Civil and Environmental Engineering."],"languages":["eng"],"rights":["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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/35081","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Margaret F. Nervegna and Cynthia Barnhart."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Civil and Environmental Engineering"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering."]},{"key":"dc:creator","label":"Author","values":["Smith, Tyler B. (Tyler Bradford)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2006-12-18T20:04:02Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2006-12-18T20:04:02Z"]},{"key":"dc:date.issued","label":"Date","values":["2006"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Civil and Environmental Engineering."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["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."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/35081"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2006.","Includes bibliographical references (p. 115-117)."]},{"key":"dc:description.abstract","label":"Abstract","values":["The field of research involving autonomous vehicles has expanded greatly over the past decade. This thesis addresses the case of a system of Unmanned Underwater Vehicles (UUVs) operating in littoral areas in an offensive capacity. A series of complementary algorithms were designed to collect information about an enemy vessell, and subsequently use this information to both select and move to a prefered intercept location that maximizes the opportunity to both re-acquire and destroy an enemy vessel. Additionally, within the context of a specifically designed simulation, key parameter changes were analyzed to determine their effectiveness to improve the system's performance as measured by four measures of effectiveness. A methodology was also designed to optimize the location of the engaging UUVs to maximize their effectiveness, and capitalize on the enemy movement within the operational area. Results are presented for both original locations and optimized locations, and initial findings provide insight into the effectiveness of the designed algorithms and statistical inference of these key parameter changes."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Decision algorithms for Unmanned Underwater Vehicles during offensive operations"]}]}],"canonical_facts":{"dc:contributor.advisor":["Margaret F. Nervegna and Cynthia Barnhart."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Civil and Environmental Engineering"],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering."],"dc:creator":["Smith, Tyler B. (Tyler Bradford)"],"dc:date.accessioned":["2006-12-18T20:04:02Z"],"dc:date.available":["2006-12-18T20:04:02Z"],"dc:date.issued":["2006"],"dc:description":["Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2006.","Includes bibliographical references (p. 115-117)."],"dc:description.abstract":["The field of research involving autonomous vehicles has expanded greatly over the past decade. This thesis addresses the case of a system of Unmanned Underwater Vehicles (UUVs) operating in littoral areas in an offensive capacity. A series of complementary algorithms were designed to collect information about an enemy vessell, and subsequently use this information to both select and move to a prefered intercept location that maximizes the opportunity to both re-acquire and destroy an enemy vessel. Additionally, within the context of a specifically designed simulation, key parameter changes were analyzed to determine their effectiveness to improve the system's performance as measured by four measures of effectiveness. A methodology was also designed to optimize the location of the engaging UUVs to maximize their effectiveness, and capitalize on the enemy movement within the operational area. Results are presented for both original locations and optimized locations, and initial findings provide insight into the effectiveness of the designed algorithms and statistical inference of these key parameter changes."],"dc:description.degree":["S.M."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/1721.1/35081"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Civil and Environmental Engineering."],"dc:title":["Decision algorithms for Unmanned Underwater Vehicles during offensive operations"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:20:46Z"}