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Self-Supervised Steering and Path Labeling for Autonomous Driving

Autonomous driving is a complex task that requires high-level hierarchical reasoning. Various solutions based on hand-crafted rules, multi-modal systems, or end-to-end learning have been proposed over time but are not quite ready to deliver the accuracy and safety necessary for real-world urban auto...

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Detalles Bibliográficos
Autores principales: Mihalea, Andrei, Samoilescu, Robert-Florian, Florea, Adina Magda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610600/
https://www.ncbi.nlm.nih.gov/pubmed/37896566
http://dx.doi.org/10.3390/s23208473
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author Mihalea, Andrei
Samoilescu, Robert-Florian
Florea, Adina Magda
author_facet Mihalea, Andrei
Samoilescu, Robert-Florian
Florea, Adina Magda
author_sort Mihalea, Andrei
collection PubMed
description Autonomous driving is a complex task that requires high-level hierarchical reasoning. Various solutions based on hand-crafted rules, multi-modal systems, or end-to-end learning have been proposed over time but are not quite ready to deliver the accuracy and safety necessary for real-world urban autonomous driving. Those methods require expensive hardware for data collection or environmental perception and are sensitive to distribution shifts, making large-scale adoption impractical. We present an approach that solely uses monocular camera inputs to generate valuable data without any supervision. Our main contributions involve a mechanism that can provide steering data annotations starting from unlabeled data alongside a different pipeline that generates path labels in a completely self-supervised manner. Thus, our method represents a natural step towards leveraging the large amounts of available online data ensuring the complexity and the diversity required to learn a robust autonomous driving policy.
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spelling pubmed-106106002023-10-28 Self-Supervised Steering and Path Labeling for Autonomous Driving Mihalea, Andrei Samoilescu, Robert-Florian Florea, Adina Magda Sensors (Basel) Article Autonomous driving is a complex task that requires high-level hierarchical reasoning. Various solutions based on hand-crafted rules, multi-modal systems, or end-to-end learning have been proposed over time but are not quite ready to deliver the accuracy and safety necessary for real-world urban autonomous driving. Those methods require expensive hardware for data collection or environmental perception and are sensitive to distribution shifts, making large-scale adoption impractical. We present an approach that solely uses monocular camera inputs to generate valuable data without any supervision. Our main contributions involve a mechanism that can provide steering data annotations starting from unlabeled data alongside a different pipeline that generates path labels in a completely self-supervised manner. Thus, our method represents a natural step towards leveraging the large amounts of available online data ensuring the complexity and the diversity required to learn a robust autonomous driving policy. MDPI 2023-10-15 /pmc/articles/PMC10610600/ /pubmed/37896566 http://dx.doi.org/10.3390/s23208473 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mihalea, Andrei
Samoilescu, Robert-Florian
Florea, Adina Magda
Self-Supervised Steering and Path Labeling for Autonomous Driving
title Self-Supervised Steering and Path Labeling for Autonomous Driving
title_full Self-Supervised Steering and Path Labeling for Autonomous Driving
title_fullStr Self-Supervised Steering and Path Labeling for Autonomous Driving
title_full_unstemmed Self-Supervised Steering and Path Labeling for Autonomous Driving
title_short Self-Supervised Steering and Path Labeling for Autonomous Driving
title_sort self-supervised steering and path labeling for autonomous driving
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610600/
https://www.ncbi.nlm.nih.gov/pubmed/37896566
http://dx.doi.org/10.3390/s23208473
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