Simultaneous Localization And Mapping: A Survey of Current Trends in Autonomous Driving. Bresson, G., Alsayed, Z., Yu, L., & Glaser, S. EEE Transactions on Intelligent Vehicles, 2(3):194-220, Institute of Electrical and Electronics Engineers, 2017. Paper Website doi abstract bibtex In this article, we propose a survey of the Simultaneous Localization And Mapping field when considering the recent evolution of autonomous driving. The growing interest regarding self-driving cars has given new directions to localization and mapping techniques. In this survey, we give an overview of the different branches of SLAM before going into the details of specific trends that are of interest when considered with autonomous applications in mind. We first present the limits of classical approaches for autonomous driving and discuss the criteria that are essential for this kind of application. We then review the methods where the identified challenges are tackled. We mostly focus on approaches building and reusing long-term maps in various conditions (weather, season, etc.). We also go through the emerging domain of multi-vehicle SLAM and its link with self-driving cars. We survey the different paradigms of that field (centralized and distributed) and the existing solutions. Finally, we conclude by giving an overview of the various large-scale experiments that have been carried out until now and discuss the remaining challenges and future orientations.
@article{
title = {Simultaneous Localization And Mapping: A Survey of Current Trends in Autonomous Driving},
type = {article},
year = {2017},
keywords = {Index Terms-SLAM,autonomous ve-hicle,drift,localization,mapping,multi-vehicle,place recognition,survey},
pages = {194-220},
volume = {2},
websites = {https://hal.archives-ouvertes.fr/hal-01615897},
publisher = {Institute of Electrical and Electronics Engineers},
id = {c2f2f85a-feb7-3993-8953-b0fe92263d1c},
created = {2022-09-07T08:35:48.062Z},
accessed = {2022-09-07},
file_attached = {true},
profile_id = {48fc0258-023d-3602-860e-824092d62c56},
group_id = {5ec9cc91-a5d6-3de5-82f3-3ef3d98a89c1},
last_modified = {2022-09-09T05:37:33.894Z},
read = {false},
starred = {false},
authored = {false},
confirmed = {false},
hidden = {false},
folder_uuids = {97693603-b330-4e3e-8cf5-d549e6474921},
private_publication = {false},
abstract = {In this article, we propose a survey of the Simultaneous Localization And Mapping field when considering the recent evolution of autonomous driving. The growing interest regarding self-driving cars has given new directions to localization and mapping techniques. In this survey, we give an overview of the different branches of SLAM before going into the details of specific trends that are of interest when considered with autonomous applications in mind. We first present the limits of classical approaches for autonomous driving and discuss the criteria that are essential for this kind of application. We then review the methods where the identified challenges are tackled. We mostly focus on approaches building and reusing long-term maps in various conditions (weather, season, etc.). We also go through the emerging domain of multi-vehicle SLAM and its link with self-driving cars. We survey the different paradigms of that field (centralized and distributed) and the existing solutions. Finally, we conclude by giving an overview of the various large-scale experiments that have been carried out until now and discuss the remaining challenges and future orientations.},
bibtype = {article},
author = {Bresson, Guillaume and Alsayed, Zayed and Yu, Li and Glaser, Sébastien},
doi = {10.1109/TIV.2017.2749181ï},
journal = {EEE Transactions on Intelligent Vehicles},
number = {3}
}
Downloads: 0
{"_id":"CB9BxABkmmxZmyims","bibbaseid":"bresson-alsayed-yu-glaser-simultaneouslocalizationandmappingasurveyofcurrenttrendsinautonomousdriving-2017","author_short":["Bresson, G.","Alsayed, Z.","Yu, L.","Glaser, S."],"bibdata":{"title":"Simultaneous Localization And Mapping: A Survey of Current Trends in Autonomous Driving","type":"article","year":"2017","keywords":"Index Terms-SLAM,autonomous ve-hicle,drift,localization,mapping,multi-vehicle,place recognition,survey","pages":"194-220","volume":"2","websites":"https://hal.archives-ouvertes.fr/hal-01615897","publisher":"Institute of Electrical and Electronics Engineers","id":"c2f2f85a-feb7-3993-8953-b0fe92263d1c","created":"2022-09-07T08:35:48.062Z","accessed":"2022-09-07","file_attached":"true","profile_id":"48fc0258-023d-3602-860e-824092d62c56","group_id":"5ec9cc91-a5d6-3de5-82f3-3ef3d98a89c1","last_modified":"2022-09-09T05:37:33.894Z","read":false,"starred":false,"authored":false,"confirmed":false,"hidden":false,"folder_uuids":"97693603-b330-4e3e-8cf5-d549e6474921","private_publication":false,"abstract":"In this article, we propose a survey of the Simultaneous Localization And Mapping field when considering the recent evolution of autonomous driving. The growing interest regarding self-driving cars has given new directions to localization and mapping techniques. In this survey, we give an overview of the different branches of SLAM before going into the details of specific trends that are of interest when considered with autonomous applications in mind. We first present the limits of classical approaches for autonomous driving and discuss the criteria that are essential for this kind of application. We then review the methods where the identified challenges are tackled. We mostly focus on approaches building and reusing long-term maps in various conditions (weather, season, etc.). We also go through the emerging domain of multi-vehicle SLAM and its link with self-driving cars. We survey the different paradigms of that field (centralized and distributed) and the existing solutions. Finally, we conclude by giving an overview of the various large-scale experiments that have been carried out until now and discuss the remaining challenges and future orientations.","bibtype":"article","author":"Bresson, Guillaume and Alsayed, Zayed and Yu, Li and Glaser, Sébastien","doi":"10.1109/TIV.2017.2749181ï","journal":"EEE Transactions on Intelligent Vehicles","number":"3","bibtex":"@article{\n title = {Simultaneous Localization And Mapping: A Survey of Current Trends in Autonomous Driving},\n type = {article},\n year = {2017},\n keywords = {Index Terms-SLAM,autonomous ve-hicle,drift,localization,mapping,multi-vehicle,place recognition,survey},\n pages = {194-220},\n volume = {2},\n websites = {https://hal.archives-ouvertes.fr/hal-01615897},\n publisher = {Institute of Electrical and Electronics Engineers},\n id = {c2f2f85a-feb7-3993-8953-b0fe92263d1c},\n created = {2022-09-07T08:35:48.062Z},\n accessed = {2022-09-07},\n file_attached = {true},\n profile_id = {48fc0258-023d-3602-860e-824092d62c56},\n group_id = {5ec9cc91-a5d6-3de5-82f3-3ef3d98a89c1},\n last_modified = {2022-09-09T05:37:33.894Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n folder_uuids = {97693603-b330-4e3e-8cf5-d549e6474921},\n private_publication = {false},\n abstract = {In this article, we propose a survey of the Simultaneous Localization And Mapping field when considering the recent evolution of autonomous driving. The growing interest regarding self-driving cars has given new directions to localization and mapping techniques. In this survey, we give an overview of the different branches of SLAM before going into the details of specific trends that are of interest when considered with autonomous applications in mind. We first present the limits of classical approaches for autonomous driving and discuss the criteria that are essential for this kind of application. We then review the methods where the identified challenges are tackled. We mostly focus on approaches building and reusing long-term maps in various conditions (weather, season, etc.). We also go through the emerging domain of multi-vehicle SLAM and its link with self-driving cars. We survey the different paradigms of that field (centralized and distributed) and the existing solutions. Finally, we conclude by giving an overview of the various large-scale experiments that have been carried out until now and discuss the remaining challenges and future orientations.},\n bibtype = {article},\n author = {Bresson, Guillaume and Alsayed, Zayed and Yu, Li and Glaser, Sébastien},\n doi = {10.1109/TIV.2017.2749181ï},\n journal = {EEE Transactions on Intelligent Vehicles},\n number = {3}\n}","author_short":["Bresson, G.","Alsayed, Z.","Yu, L.","Glaser, S."],"urls":{"Paper":"https://bibbase.org/service/mendeley/bfbbf840-4c42-3914-a463-19024f50b30c/file/369402b7-d883-e621-23f7-177e4be416be/full_text.pdf.pdf","Website":"https://hal.archives-ouvertes.fr/hal-01615897"},"biburl":"https://bibbase.org/service/mendeley/bfbbf840-4c42-3914-a463-19024f50b30c","bibbaseid":"bresson-alsayed-yu-glaser-simultaneouslocalizationandmappingasurveyofcurrenttrendsinautonomousdriving-2017","role":"author","keyword":["Index Terms-SLAM","autonomous ve-hicle","drift","localization","mapping","multi-vehicle","place recognition","survey"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"article","biburl":"https://bibbase.org/service/mendeley/bfbbf840-4c42-3914-a463-19024f50b30c","dataSources":["2252seNhipfTmjEBQ"],"keywords":["index terms-slam","autonomous ve-hicle","drift","localization","mapping","multi-vehicle","place recognition","survey"],"search_terms":["simultaneous","localization","mapping","survey","current","trends","autonomous","driving","bresson","alsayed","yu","glaser"],"title":"Simultaneous Localization And Mapping: A Survey of Current Trends in Autonomous Driving","year":2017}