2026-09-19T01:16:39Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1283462021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Daniela Rus.
Ort, Moses Teddy.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2020-11-03T20:32:09Z
2020-11-03T20:32:09Z
2020
2020
https://hdl.handle.net/1721.1/128346
1201969047
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 69-73).
Most autonomous vehicle systems currently rely on high-definition prior maps in order to localize and navigate in their environment. In this work, we present MapLite: a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are used to segment the road region and register the topometric map in order to fuse the high-level navigation goals with a variational path planner in the vehicle frame. This enables the system to plan trajectories that correctly navigate road intersections without the use of an external localization system such as GPS or a detailed prior map. Since the topometric maps already exist for the vast majority of roads, this solution greatly increases the geographical scope for autonomous mobility solutions. We implement MapLite on a full-scale autonomous vehicle and exhaustively test it on over 15km of real-world driving including over 100 autonomous intersection traversals. We further extend these results through simulated testing to validate the system on complex road junction topologies such as traffic circles.
by Teddy Ort.
S.M.
S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
73 pages
eng
Massachusetts Institute of Technology
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
Electrical Engineering and Computer Science.
MapLite : autonomous navigation in rural environments without detailed prior maps
Autonomous navigation in rural environments without detailed prior maps
Thesis
application/pdf
2020-11-03T20:32:08Z
Publication
Master
EECS
unknown
unknown
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<Abstract>Most autonomous vehicle systems currently rely on high-definition prior maps in order to localize and navigate in their environment. In this work, we present MapLite: a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are used to segment the road region and register the topometric map in order to fuse the high-level navigation goals with a variational path planner in the vehicle frame. This enables the system to plan trajectories that correctly navigate road intersections without the use of an external localization system such as GPS or a detailed prior map. Since the topometric maps already exist for the vast majority of roads, this solution greatly increases the geographical scope for autonomous mobility solutions. We implement MapLite on a full-scale autonomous vehicle and exhaustively test it on over 15km of real-world driving including over 100 autonomous intersection traversals. We further extend these results through simulated testing to validate the system on complex road junction topologies such as traffic circles.</Abstract>
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