Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion

Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrastructure demands, poses challenges for widespread a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2024 IEEE International Conference on Robotics and Automation (ICRA) S. 11934 - 11940
Hauptverfasser: He, Jinhao, Huang, Huaiyang, Zhang, Shuyang, Jiao, Jianhao, Liu, Chengju, Liu, Ming
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 13.05.2024
Schlagworte:
Cameras
Laser radar
Localization
Location awareness
Robot vision systems
Robotics in Under-Resourced Settings
Robustness
Sensor Fusion
Sensor systems
Visualization
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrastructure demands, poses challenges for widespread adoption in mass-market applications. In this paper, we aim to use only a monocular camera to achieve comparable onboard localization performance by tracking deep-learning visual features on a LiDAR-enhanced visual prior map. Experiments show that the proposed algorithm can provide centimeter-level global positioning results with scale, which is effortlessly integrated and favorable for low-cost robot system deployment in real-world applications.
AbstractList Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrastructure demands, poses challenges for widespread adoption in mass-market applications. In this paper, we aim to use only a monocular camera to achieve comparable onboard localization performance by tracking deep-learning visual features on a LiDAR-enhanced visual prior map. Experiments show that the proposed algorithm can provide centimeter-level global positioning results with scale, which is effortlessly integrated and favorable for low-cost robot system deployment in real-world applications.
Author Jiao, Jianhao
Liu, Chengju
Zhang, Shuyang
Liu, Ming
He, Jinhao
Huang, Huaiyang
Author_xml – sequence: 1
  givenname: Jinhao
  surname: He
  fullname: He, Jinhao
  organization: The Hong Kong University of Science and Technology (Guangzhou),Thrust of Robotics and Autonomous Systems,Guangzhou,China
– sequence: 2
  givenname: Huaiyang
  surname: Huang
  fullname: Huang, Huaiyang
  organization: Baidu Autonomous Driving Technology Department (ADT)
– sequence: 3
  givenname: Shuyang
  surname: Zhang
  fullname: Zhang, Shuyang
  organization: The Hong Kong University of Science and Technology,Department of Electronic and Computer Engineering,Clear Water Bay, Kowloon,Hong Kong
– sequence: 4
  givenname: Jianhao
  surname: Jiao
  fullname: Jiao, Jianhao
  email: ucacjji@ucl.ac.uk
  organization: The Hong Kong University of Science and Technology,Department of Electronic and Computer Engineering,Clear Water Bay, Kowloon,Hong Kong
– sequence: 5
  givenname: Chengju
  surname: Liu
  fullname: Liu, Chengju
  organization: Tongji University,School of Electronics and Information Engineering,Shanghai,China
– sequence: 6
  givenname: Ming
  surname: Liu
  fullname: Liu, Ming
  organization: The Hong Kong University of Science and Technology (Guangzhou),Thrust of Robotics and Autonomous Systems,Guangzhou,China
BookMark eNo1j99KwzAcRiO4C517A8G8QGv-NsllqVYHlY0xr0eaJfqDmkjaIr69BfXqwDnwwXeNLmOKHqE7SkpKibnfNodaKipUyQgTJSUVXby8QBujjOaScC2kEleorZ2bs5083mdIuXA-ThkcfkkxuXmwGe_TCBOkCPENf8H0jnchDBA97uChPuB2Hpd4g1bBDqPf_HGNXtvHY_NcdLunbVN3BVBVTYWQPDBdKRN48MQaGhh3VLCweNUzo8-6Z9IyqnQle66EslZqE0zPz5J5ztfo9ncXvPenzwwfNn-f_u_xHxmgSS0
ContentType Conference Proceeding
DBID 6IE
6IH
CBEJK
RIE
RIO
DOI 10.1109/ICRA57147.2024.10611105
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan (POP) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE/IET Electronic Library
IEEE Proceedings Order Plans (POP) 1998-present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9798350384574
EndPage 11940
ExternalDocumentID 10611105
Genre orig-research
GrantInformation_xml – fundername: National Natural Science Foundation of China
  funderid: 10.13039/501100001809
GroupedDBID 6IE
6IH
CBEJK
RIE
RIO
ID FETCH-LOGICAL-i176t-453f28679f3fe0a91f23c142f53f7b298d8b25a217865b3747aa589f9b3d52e33
IEDL.DBID RIE
ISICitedReferencesCount 1
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001369728002067&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Aug 14 05:40:32 EDT 2024
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i176t-453f28679f3fe0a91f23c142f53f7b298d8b25a217865b3747aa589f9b3d52e33
PageCount 7
ParticipantIDs ieee_primary_10611105
PublicationCentury 2000
PublicationDate 2024-May-13
PublicationDateYYYYMMDD 2024-05-13
PublicationDate_xml – month: 05
  year: 2024
  text: 2024-May-13
  day: 13
PublicationDecade 2020
PublicationTitle 2024 IEEE International Conference on Robotics and Automation (ICRA)
PublicationTitleAbbrev ICRA
PublicationYear 2024
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.8921771
Snippet Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization...
SourceID ieee
SourceType Publisher
StartPage 11934
SubjectTerms Cameras
Laser radar
Localization
Location awareness
Robot vision systems
Robotics in Under-Resourced Settings
Robustness
Sensor Fusion
Sensor systems
Visualization
Title Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion
URI https://ieeexplore.ieee.org/document/10611105
WOSCitedRecordID wos001369728002067&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA62ePCkYsU3OXhN27w2ybFUFwWppSj0VpJsAnvpSu36-52kq-LBg7eQByETwnwz-WYGodsq8shYCEQ6oYgQjBKrLIN3JYMubMGt8bnYhJrN9HJp5l2weo6FCSFk8lkYpmb-y68a3yZX2SiZL6CuZA_1lCp2wVodZ4uOzehxuphIRYUCs4-J4dfsX3VTstooD_-54REa_ATg4fm3ajlGe2F9gsqJ923K7ABDdbMhmVdZewzPsslsUjzvGFiwBicHK36OMcFI_FTfTRa4bJNrbIBey_uX6QPpyiCQmqpiS4QEcaa8eCDWMLaGRsY9FSxCv3LM6Eo7Ji3YFrqQjoN9YK3UJhrHK8kC56eov27W4QxhgNMWEIougpXCUaMBrVQuJbGrtAUocY4GSQirt12mi9XX-S_-6L9EB0nU6Ted8ivU327acI32_ce2ft_c5Pv5BA_SkOI
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELagIMEEiCLeeGBNqV-xPVaFqBWlVFWRulW240hZGlQafj9nNwUxMLBZdpwoZ1n33d13dwjd5wUrKPU-EZbLhHNKEiMNhXslvEpNyox2sdmEHI_VfK4nTbJ6zIXx3kfyme-EYYzl55Wrg6vsIZgvoK7ELtoT8NruJl2rYW2Rrn4Y9qc9IQmXYPhR3tk-_6tzSlQc2dE_P3mM2j8peHjyrVxO0I5fnqKs51wdajvAUlmtksisLB2Gi1lFPimeNBws2IODixW_FkUAknhUPvamOKuDc6yN3rKnWX-QNI0QkpLIdJ1wAQINlfFAsL5rNCkoc4TTAualpVrlylJhwLpQqbAMLARjhNKFtiwX1DN2hlrLaunPEQZAbQCjqNQbwS3RCvBKbkMZu1wZABMXqB2EsHjf1LpYbP__8o_5O3QwmL2MFqPh-PkKHQaxh9g6YdeotV7V_gbtu891-bG6jWf1BcxFlCk
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2024+IEEE+International+Conference+on+Robotics+and+Automation+%28ICRA%29&rft.atitle=Accurate+Prior-centric+Monocular+Positioning+with+Offline+LiDAR+Fusion&rft.au=He%2C+Jinhao&rft.au=Huang%2C+Huaiyang&rft.au=Zhang%2C+Shuyang&rft.au=Jiao%2C+Jianhao&rft.date=2024-05-13&rft.pub=IEEE&rft.spage=11934&rft.epage=11940&rft_id=info:doi/10.1109%2FICRA57147.2024.10611105&rft.externalDocID=10611105