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Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck

Road boundary detection is an important part of the perception of the autonomous driving. It is difficult to detect road boundaries of unstructured roads because there are no curbs. There are no clear boundaries on mine roads to distinguish areas within the road boundary line and areas outside the r...

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Detalles Bibliográficos
Autores principales: Lu, Xiaowei, Ai, Yunfeng, Tian, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070413/
https://www.ncbi.nlm.nih.gov/pubmed/32085668
http://dx.doi.org/10.3390/s20041121
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author Lu, Xiaowei
Ai, Yunfeng
Tian, Bin
author_facet Lu, Xiaowei
Ai, Yunfeng
Tian, Bin
author_sort Lu, Xiaowei
collection PubMed
description Road boundary detection is an important part of the perception of the autonomous driving. It is difficult to detect road boundaries of unstructured roads because there are no curbs. There are no clear boundaries on mine roads to distinguish areas within the road boundary line and areas outside the road boundary line. This paper proposes a real-time road boundary detection and tracking method by a 3D-LIDAR sensor. The road boundary points are extracted from the detected elevated point clouds above the ground point cloud according to the spatial distance characteristics and the angular features. Road tracking is to predict and update the boundary point information in real-time, in order to prevent false and missed detection. The experimental verification of mine road data shows the accuracy and robustness of the proposed algorithm.
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spelling pubmed-70704132020-03-19 Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck Lu, Xiaowei Ai, Yunfeng Tian, Bin Sensors (Basel) Article Road boundary detection is an important part of the perception of the autonomous driving. It is difficult to detect road boundaries of unstructured roads because there are no curbs. There are no clear boundaries on mine roads to distinguish areas within the road boundary line and areas outside the road boundary line. This paper proposes a real-time road boundary detection and tracking method by a 3D-LIDAR sensor. The road boundary points are extracted from the detected elevated point clouds above the ground point cloud according to the spatial distance characteristics and the angular features. Road tracking is to predict and update the boundary point information in real-time, in order to prevent false and missed detection. The experimental verification of mine road data shows the accuracy and robustness of the proposed algorithm. MDPI 2020-02-18 /pmc/articles/PMC7070413/ /pubmed/32085668 http://dx.doi.org/10.3390/s20041121 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lu, Xiaowei
Ai, Yunfeng
Tian, Bin
Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck
title Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck
title_full Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck
title_fullStr Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck
title_full_unstemmed Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck
title_short Real-Time Mine Road Boundary Detection and Tracking for Autonomous Truck
title_sort real-time mine road boundary detection and tracking for autonomous truck
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070413/
https://www.ncbi.nlm.nih.gov/pubmed/32085668
http://dx.doi.org/10.3390/s20041121
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