Curb-intersection feature based Monte Carlo Localization on urban roads
One of the most prominent features on an urban road is the curb, which defines the boundary of a road surface. An intersection is a junction of two or more roads, appearing where no curb exists. The combination of curb and intersection features and their idiosyncrasies carry significant information...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2013
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| Online Access: | http://hdl.handle.net/1721.1/81465 https://orcid.org/0000-0001-5473-3566 https://orcid.org/0000-0002-0505-1400 |
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| author | Qin, B. Chong, Z. J. Ang, M. H. Frazzoli, Emilio Rus, Daniela L. Bandyopadhyay, Tirthankar |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Qin, B. Chong, Z. J. Ang, M. H. Frazzoli, Emilio Rus, Daniela L. Bandyopadhyay, Tirthankar |
| author_sort | Qin, B. |
| collection | MIT |
| description | One of the most prominent features on an urban road is the curb, which defines the boundary of a road surface. An intersection is a junction of two or more roads, appearing where no curb exists. The combination of curb and intersection features and their idiosyncrasies carry significant information about the urban road network that can be exploited to improve a vehicle's localization. This paper introduces a Monte Carlo Localization (MCL) method using the curb-intersection features on urban roads. We propose a novel idea of “Virtual LIDAR” to get the measurement models for these features. Under the MCL framework, above road observation is fused with odometry information, which is able to yield precise localization. We implement the system using a single tilted 2D LIDAR on our autonomous test bed and show robust performance in the presence of occlusion from other vehicles and pedestrians. |
| first_indexed | 2024-09-23T12:29:44Z |
| format | Article |
| id | mit-1721.1/81465 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:29:44Z |
| publishDate | 2013 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/814652022-10-01T09:21:44Z Curb-intersection feature based Monte Carlo Localization on urban roads Qin, B. Chong, Z. J. Ang, M. H. Frazzoli, Emilio Rus, Daniela L. Bandyopadhyay, Tirthankar Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Frazzoli, Emilio Rus, Daniela L. Bandyopadhyay, Tirthankar One of the most prominent features on an urban road is the curb, which defines the boundary of a road surface. An intersection is a junction of two or more roads, appearing where no curb exists. The combination of curb and intersection features and their idiosyncrasies carry significant information about the urban road network that can be exploited to improve a vehicle's localization. This paper introduces a Monte Carlo Localization (MCL) method using the curb-intersection features on urban roads. We propose a novel idea of “Virtual LIDAR” to get the measurement models for these features. Under the MCL framework, above road observation is fused with odometry information, which is able to yield precise localization. We implement the system using a single tilted 2D LIDAR on our autonomous test bed and show robust performance in the presence of occlusion from other vehicles and pedestrians. 2013-10-21T18:33:47Z 2013-10-21T18:33:47Z 2012-05 Article http://purl.org/eprint/type/ConferencePaper 978-1-4673-1405-3 978-1-4673-1403-9 978-1-4673-1578-4 978-1-4673-1404-6 http://hdl.handle.net/1721.1/81465 Qin, B., Z. J. Chong, T. Bandyopadhyay, M. H. Ang, E. Frazzoli, and D. Rus. “Curb-intersection feature based Monte Carlo Localization on urban roads.” In 2012 IEEE International Conference on Robotics and Automation, 2640-2646. Institute of Electrical and Electronics Engineers, 2012. https://orcid.org/0000-0001-5473-3566 https://orcid.org/0000-0002-0505-1400 en_US http://dx.doi.org/10.1109/ICRA.2012.6224913 Proceedings of the 2012 IEEE International Conference on Robotics and Automation Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT web domain |
| spellingShingle | Qin, B. Chong, Z. J. Ang, M. H. Frazzoli, Emilio Rus, Daniela L. Bandyopadhyay, Tirthankar Curb-intersection feature based Monte Carlo Localization on urban roads |
| title | Curb-intersection feature based Monte Carlo Localization on urban roads |
| title_full | Curb-intersection feature based Monte Carlo Localization on urban roads |
| title_fullStr | Curb-intersection feature based Monte Carlo Localization on urban roads |
| title_full_unstemmed | Curb-intersection feature based Monte Carlo Localization on urban roads |
| title_short | Curb-intersection feature based Monte Carlo Localization on urban roads |
| title_sort | curb intersection feature based monte carlo localization on urban roads |
| url | http://hdl.handle.net/1721.1/81465 https://orcid.org/0000-0001-5473-3566 https://orcid.org/0000-0002-0505-1400 |
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