Autonomous data collection techniques for approximating marine vehicle kinematics
Thesis: S.M. in Naval Architecture and Marine Engineering, and S.M. in Ocean Engineering, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2015
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| Online Access: | http://hdl.handle.net/1721.1/100132 |
| _version_ | 1826188182297772032 |
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| author | Gerlach, Jacob |
| author2 | Michael R. Benjamin and John J. Leonard. |
| author_facet | Michael R. Benjamin and John J. Leonard. Gerlach, Jacob |
| author_sort | Gerlach, Jacob |
| collection | MIT |
| description | Thesis: S.M. in Naval Architecture and Marine Engineering, and S.M. in Ocean Engineering, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. |
| first_indexed | 2024-09-23T07:55:48Z |
| format | Thesis |
| id | mit-1721.1/100132 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T07:55:48Z |
| publishDate | 2015 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1001322022-01-13T07:54:05Z Autonomous data collection techniques for approximating marine vehicle kinematics Gerlach, Jacob Michael R. Benjamin and John J. Leonard. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering Mechanical Engineering. Thesis: S.M. in Naval Architecture and Marine Engineering, and S.M. in Ocean Engineering, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 75-77). Understanding vehicle kinematics is essential in allowing autonomous guidance algorithms to accurately assess short range encounters. Low cost, reconfigurable autonomous vehicles motivate using in-field online techniques rather than tow tank testing or Computational Fluid Dynamics (CFD). While the parameters of many physical dynamic models can be obtained using System Identification (SI) techniques, these models require knowledge of the vehicle actuators, which may not be the case in a "backseat driver" architecture using payload autonomy. Even when an identified physical model is available, using it to simulate trajectories requires insight into the design of the relevant controller, which may be proprietary or otherwise unknown to the back seat. This thesis develops a data collection procedure to obtain empirical kinematic trajectories for unmanned surface vehicles (USVs). A linear black box model of the USV yaw system is also developed, using only data available in the backseat. A prediction table for the M200 USV is developed with both techniques. by Jacob Gerlach. S.M. in Naval Architecture and Marine Engineering, and S.M. in Ocean Engineering 2015-12-03T20:55:25Z 2015-12-03T20:55:25Z 2015 2015 Thesis http://hdl.handle.net/1721.1/100132 930036068 eng 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 77 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Gerlach, Jacob Autonomous data collection techniques for approximating marine vehicle kinematics |
| title | Autonomous data collection techniques for approximating marine vehicle kinematics |
| title_full | Autonomous data collection techniques for approximating marine vehicle kinematics |
| title_fullStr | Autonomous data collection techniques for approximating marine vehicle kinematics |
| title_full_unstemmed | Autonomous data collection techniques for approximating marine vehicle kinematics |
| title_short | Autonomous data collection techniques for approximating marine vehicle kinematics |
| title_sort | autonomous data collection techniques for approximating marine vehicle kinematics |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/100132 |
| work_keys_str_mv | AT gerlachjacob autonomousdatacollectiontechniquesforapproximatingmarinevehiclekinematics |