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Radar Sensing for Intelligent Vehicles in Urban Environments
Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507681/ https://www.ncbi.nlm.nih.gov/pubmed/26102493 http://dx.doi.org/10.3390/s150614661 |
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author | Reina, Giulio Johnson, David Underwood, James |
author_facet | Reina, Giulio Johnson, David Underwood, James |
author_sort | Reina, Giulio |
collection | PubMed |
description | Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the sensor frame, without the need for a separate synchronised navigation source, calibration parameters describing the location of the radar in the vehicle frame, or the geometric restrictions made in the previous main method in the field. Experimental results are presented in various urban scenarios to validate this approach, showing its potential applicability for advanced driving assistance systems and autonomous vehicle operations. |
format | Online Article Text |
id | pubmed-4507681 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-45076812015-07-22 Radar Sensing for Intelligent Vehicles in Urban Environments Reina, Giulio Johnson, David Underwood, James Sensors (Basel) Article Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the sensor frame, without the need for a separate synchronised navigation source, calibration parameters describing the location of the radar in the vehicle frame, or the geometric restrictions made in the previous main method in the field. Experimental results are presented in various urban scenarios to validate this approach, showing its potential applicability for advanced driving assistance systems and autonomous vehicle operations. MDPI 2015-06-19 /pmc/articles/PMC4507681/ /pubmed/26102493 http://dx.doi.org/10.3390/s150614661 Text en © 2015 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 license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Reina, Giulio Johnson, David Underwood, James Radar Sensing for Intelligent Vehicles in Urban Environments |
title | Radar Sensing for Intelligent Vehicles in Urban Environments |
title_full | Radar Sensing for Intelligent Vehicles in Urban Environments |
title_fullStr | Radar Sensing for Intelligent Vehicles in Urban Environments |
title_full_unstemmed | Radar Sensing for Intelligent Vehicles in Urban Environments |
title_short | Radar Sensing for Intelligent Vehicles in Urban Environments |
title_sort | radar sensing for intelligent vehicles in urban environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507681/ https://www.ncbi.nlm.nih.gov/pubmed/26102493 http://dx.doi.org/10.3390/s150614661 |
work_keys_str_mv | AT reinagiulio radarsensingforintelligentvehiclesinurbanenvironments AT johnsondavid radarsensingforintelligentvehiclesinurbanenvironments AT underwoodjames radarsensingforintelligentvehiclesinurbanenvironments |