2026-09-20T11:36:53Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/350812022-01-13T07:54:23Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Margaret F. Nervegna and Cynthia Barnhart.
Smith, Tyler B. (Tyler Bradford)
Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
2006-12-18T20:04:02Z
2006-12-18T20:04:02Z
2006
2006
http://hdl.handle.net/1721.1/35081
71271507
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2006.
Includes bibliographical references (p. 115-117).
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.
by Tyler B. Smith.
S.M.
117 p.
15141342 bytes
15140838 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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.
http://dspace.mit.edu/handle/1721.1/7582
Civil and Environmental Engineering.
Decision algorithms for Unmanned Underwater Vehicles during offensive operations
Decision algorithms for UUVs during offensive operations
Thesis
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Publication
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<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>
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