Toward robust active semantic SLAM via Max-Mixtures
Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2020
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| Online Access: | https://hdl.handle.net/1721.1/127041 |
| _version_ | 1811077461519106048 |
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| author | Baxter, David P.,Nav. E.(David Paul)Massachusetts Institute of Technology. |
| author2 | John J. Leonard. |
| author_facet | John J. Leonard. Baxter, David P.,Nav. E.(David Paul)Massachusetts Institute of Technology. |
| author_sort | Baxter, David P.,Nav. E.(David Paul)Massachusetts Institute of Technology. |
| collection | MIT |
| description | Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020 |
| first_indexed | 2024-09-23T10:43:24Z |
| format | Thesis |
| id | mit-1721.1/127041 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:43:24Z |
| publishDate | 2020 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1270412020-09-04T03:33:03Z Toward robust active semantic SLAM via Max-Mixtures Toward robust active semantic simultaneous localization and mapping via Max-Mixtures Baxter, David P.,Nav. E.(David Paul)Massachusetts Institute of Technology. John J. Leonard. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering Mechanical Engineering. Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020 Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020 Cataloged from the official PDF of thesis. Includes bibliographical references (pages 75-78). In a step towards the level of autonomy seen in humans, this work attempts to emulate a high level and low level approach to world representation and short term adaptation. Specifically, this work demonstrates an implementation of robotic perception that transforms stereo camera and LIDAR sensor data into a sparse map of semantic objects and a locally consistent flexible occupancy grid. This provides a topological representation for grouping objects into higher level classes and a geometric map for traditional planning. Additionally, a reactive dynamic window obstacle avoidance system is shown to quickly plan short term trajectories that avoid both static and dynamic objects while progressing towards a goal. To combine computational efficiency with the robust advantages of multimodal inference, this work uses Semantic Max Mixture factors to approximate multimodal belief in a manner compatible to nonlinear least squares solvers. Experimental results are presented using a RACECAR mobile robot operating in several hallways of MIT, using AprilTags as surrogates for objects in the Semantic Max Mixtures Algorithm. Future work will seek to further integrate the components to create a closed-loop active semantic navigation and mapping algorithm. by David P. Baxter. Nav. E. S.M. Nav.E. Massachusetts Institute of Technology, Department of Mechanical Engineering S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering 2020-09-03T17:43:40Z 2020-09-03T17:43:40Z 2020 2020 Thesis https://hdl.handle.net/1721.1/127041 1191698733 eng MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 78 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Baxter, David P.,Nav. E.(David Paul)Massachusetts Institute of Technology. Toward robust active semantic SLAM via Max-Mixtures |
| title | Toward robust active semantic SLAM via Max-Mixtures |
| title_full | Toward robust active semantic SLAM via Max-Mixtures |
| title_fullStr | Toward robust active semantic SLAM via Max-Mixtures |
| title_full_unstemmed | Toward robust active semantic SLAM via Max-Mixtures |
| title_short | Toward robust active semantic SLAM via Max-Mixtures |
| title_sort | toward robust active semantic slam via max mixtures |
| topic | Mechanical Engineering. |
| url | https://hdl.handle.net/1721.1/127041 |
| work_keys_str_mv | AT baxterdavidpnavedavidpaulmassachusettsinstituteoftechnology towardrobustactivesemanticslamviamaxmixtures AT baxterdavidpnavedavidpaulmassachusettsinstituteoftechnology towardrobustactivesemanticsimultaneouslocalizationandmappingviamaxmixtures |