MapLite : autonomous navigation in rural environments without detailed prior maps
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...
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ndltd-MIT-oai-dspace.mit.edu-1721.1-1283462020-11-05T05:10:06Z MapLite : autonomous navigation in rural environments without detailed prior maps Autonomous navigation in rural environments without detailed prior maps Ort, Moses Teddy. Daniela Rus. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. 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 2020-11-03T20:32:09Z 2020-11-03T20:32:09Z 2020 2020 Thesis https://hdl.handle.net/1721.1/128346 1201969047 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 73 pages application/pdf Massachusetts Institute of Technology |
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Electrical Engineering and Computer Science. Ort, Moses Teddy. MapLite : autonomous navigation in rural environments without detailed prior maps |
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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 |
author2 |
Daniela Rus. |
author_facet |
Daniela Rus. Ort, Moses Teddy. |
author |
Ort, Moses Teddy. |
author_sort |
Ort, Moses Teddy. |
title |
MapLite : autonomous navigation in rural environments without detailed prior maps |
title_short |
MapLite : autonomous navigation in rural environments without detailed prior maps |
title_full |
MapLite : autonomous navigation in rural environments without detailed prior maps |
title_fullStr |
MapLite : autonomous navigation in rural environments without detailed prior maps |
title_full_unstemmed |
MapLite : autonomous navigation in rural environments without detailed prior maps |
title_sort |
maplite : autonomous navigation in rural environments without detailed prior maps |
publisher |
Massachusetts Institute of Technology |
publishDate |
2020 |
url |
https://hdl.handle.net/1721.1/128346 |
work_keys_str_mv |
AT ortmosesteddy mapliteautonomousnavigationinruralenvironmentswithoutdetailedpriormaps AT ortmosesteddy autonomousnavigationinruralenvironmentswithoutdetailedpriormaps |
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1719354888239972352 |