Object localization and identification for autonomous operation of surface marine vehicles
Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/104299 |
| _version_ | 1826212827912732672 |
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| author | Mentzelos, Konstantinos |
| author2 | Chryssostomos Chryssostomidis, Chathan Cooke and Joe Harbour. |
| author_facet | Chryssostomos Chryssostomidis, Chathan Cooke and Joe Harbour. Mentzelos, Konstantinos |
| author_sort | Mentzelos, Konstantinos |
| collection | MIT |
| description | Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. |
| first_indexed | 2024-09-23T15:38:33Z |
| format | Thesis |
| id | mit-1721.1/104299 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T15:38:33Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1042992019-04-12T16:22:59Z Object localization and identification for autonomous operation of surface marine vehicles Mentzelos, Konstantinos Chryssostomos Chryssostomidis, Chathan Cooke and Joe Harbour. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Mechanical Engineering. Electrical Engineering and Computer Science. Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. "June 2016." Cataloged from PDF version of thesis. Includes bibliographical references (pages 99-100). A method for autonomous navigation of surface marine vehicles is developed A camera video stream is utilized as input to achieve object localization and identification by application of state-of-the-art Machine Learning algorithms. In particular, deep Convolutional Neural Networks are first trained offline using a collection of images of possible objects to be encountered (navy ships, sail boats, power boats, buoys, bridges, etc.). The trained network applied to new images returns real-time classification predictions with more than 93% accuracy. This information, along with distance and heading relative to the objects taken from the calibrated camera, allows for the precise determination of vehicle position with respect to its surrounding environment and is used to compute safe maneuvering and path planning strategy that conforms to the established marine navigation rules. These algorithms can be used in association with existing tools, such as LiDAR and GPS, to enable a completely autonomous marine vehicle. by Konstantinos Mentzelos. Nav. E. S.M. 2016-09-13T19:22:58Z 2016-09-13T19:22:58Z 2016 Thesis http://hdl.handle.net/1721.1/104299 958163374 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 100 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Electrical Engineering and Computer Science. Mentzelos, Konstantinos Object localization and identification for autonomous operation of surface marine vehicles |
| title | Object localization and identification for autonomous operation of surface marine vehicles |
| title_full | Object localization and identification for autonomous operation of surface marine vehicles |
| title_fullStr | Object localization and identification for autonomous operation of surface marine vehicles |
| title_full_unstemmed | Object localization and identification for autonomous operation of surface marine vehicles |
| title_short | Object localization and identification for autonomous operation of surface marine vehicles |
| title_sort | object localization and identification for autonomous operation of surface marine vehicles |
| topic | Mechanical Engineering. Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/104299 |
| work_keys_str_mv | AT mentzeloskonstantinos objectlocalizationandidentificationforautonomousoperationofsurfacemarinevehicles |