Evaluation and testing system for automotive LiDAR sensors
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/81759 |
Resumo: | The world is facing a great technological transformation towards fully autonomous vehicles, where optimists predict that by 2030 autonomous vehicles will be sufficiently reliable, affordable, and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all their surroundings, with light detection and ranging (LiDAR) sensors being a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely on accurate measurements of the environment. Thus, these intelligent sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors, with the main goal of testing both commercially available sensors and new sensor prototypes currently under development in Bosch Car Multimedia Portugal. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment in which such devices normally operate. To characterize and validate the sensor under test, the platform evaluates several parameters, such as the field of view (FoV), angular resolution, sensor’s range, etc., based only on the point cloud output. This project is the result of a partnership between the University of Minho and Bosch Car Multimedia Portugal. |
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Evaluation and testing system for automotive LiDAR sensorsAutonomous drivingLiDAR sensorsPerception systemsEvaluation and testingEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaScience & TechnologyIndústria, inovação e infraestruturasThe world is facing a great technological transformation towards fully autonomous vehicles, where optimists predict that by 2030 autonomous vehicles will be sufficiently reliable, affordable, and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all their surroundings, with light detection and ranging (LiDAR) sensors being a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely on accurate measurements of the environment. Thus, these intelligent sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors, with the main goal of testing both commercially available sensors and new sensor prototypes currently under development in Bosch Car Multimedia Portugal. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment in which such devices normally operate. To characterize and validate the sensor under test, the platform evaluates several parameters, such as the field of view (FoV), angular resolution, sensor’s range, etc., based only on the point cloud output. This project is the result of a partnership between the University of Minho and Bosch Car Multimedia Portugal.This work was supported by the European Structural and Investment Funds in the FEDER component through the Operational Competitiveness and Internationalization Programme (COM-PETE 2020), Project nº 037902, Funding Reference POCI-01-0247-FEDER-037902.MDPIUniversidade do MinhoGomes, Tiago Manuel RibeiroRoriz, Ricardo João ReiCunha, LuísGanal, AndreasSoares, NarcisoAraújo, TeresaMonteiro, João L.2022-12-182022-12-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/81759eng2076-341710.3390/app122413003https://www.mdpi.com/2076-3417/12/24/13003info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:02:07Zoai:repositorium.sdum.uminho.pt:1822/81759Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:52:05.793346Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Evaluation and testing system for automotive LiDAR sensors |
title |
Evaluation and testing system for automotive LiDAR sensors |
spellingShingle |
Evaluation and testing system for automotive LiDAR sensors Gomes, Tiago Manuel Ribeiro Autonomous driving LiDAR sensors Perception systems Evaluation and testing Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology Indústria, inovação e infraestruturas |
title_short |
Evaluation and testing system for automotive LiDAR sensors |
title_full |
Evaluation and testing system for automotive LiDAR sensors |
title_fullStr |
Evaluation and testing system for automotive LiDAR sensors |
title_full_unstemmed |
Evaluation and testing system for automotive LiDAR sensors |
title_sort |
Evaluation and testing system for automotive LiDAR sensors |
author |
Gomes, Tiago Manuel Ribeiro |
author_facet |
Gomes, Tiago Manuel Ribeiro Roriz, Ricardo João Rei Cunha, Luís Ganal, Andreas Soares, Narciso Araújo, Teresa Monteiro, João L. |
author_role |
author |
author2 |
Roriz, Ricardo João Rei Cunha, Luís Ganal, Andreas Soares, Narciso Araújo, Teresa Monteiro, João L. |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Gomes, Tiago Manuel Ribeiro Roriz, Ricardo João Rei Cunha, Luís Ganal, Andreas Soares, Narciso Araújo, Teresa Monteiro, João L. |
dc.subject.por.fl_str_mv |
Autonomous driving LiDAR sensors Perception systems Evaluation and testing Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology Indústria, inovação e infraestruturas |
topic |
Autonomous driving LiDAR sensors Perception systems Evaluation and testing Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology Indústria, inovação e infraestruturas |
description |
The world is facing a great technological transformation towards fully autonomous vehicles, where optimists predict that by 2030 autonomous vehicles will be sufficiently reliable, affordable, and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all their surroundings, with light detection and ranging (LiDAR) sensors being a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely on accurate measurements of the environment. Thus, these intelligent sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors, with the main goal of testing both commercially available sensors and new sensor prototypes currently under development in Bosch Car Multimedia Portugal. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment in which such devices normally operate. To characterize and validate the sensor under test, the platform evaluates several parameters, such as the field of view (FoV), angular resolution, sensor’s range, etc., based only on the point cloud output. This project is the result of a partnership between the University of Minho and Bosch Car Multimedia Portugal. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-12-18 2022-12-18T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/81759 |
url |
https://hdl.handle.net/1822/81759 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2076-3417 10.3390/app122413003 https://www.mdpi.com/2076-3417/12/24/13003 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132296113029120 |