Tightly Coupled Integration of GNSS/UWB/VIO for Reliable and Seamless Positioning
The technology of autonomous vehicle (AV) is critical in nowadays Intelligent Transportation Systems. To achieve the fully automated operation for AVs, one important prerequisite is the accurate and reliable seamless localization covering complex outdoor-indoor scenarios. Although many solutions hav...
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description | The technology of autonomous vehicle (AV) is critical in nowadays Intelligent Transportation Systems. To achieve the fully automated operation for AVs, one important prerequisite is the accurate and reliable seamless localization covering complex outdoor-indoor scenarios. Although many solutions have been proposed to support AV localization, it is still challenging inon achieving reliableglobally drift-free positioning in seamless urbanthe unknown outdoor-indoor environments. With the current on-board sensors such as( GNSS, IMU, LiDAR, and cameras, etc.), it is difficult for AVs to achieve accurate drift-free indoor positioning and smooth indoor-outdoor transition due to the lack of GNSS indoorssignals in indoor environments. Meanwhile, challenges remain in reliable navigation under obscured conditions. In this paper, we propose a tightly coupled integration algorithm of GNSS RTK, Ultra-Wide Band (UWB) and Visual Inertial Odometry (VIO) to enhance the accuracy and reliability for AVs seamless localization in challengingharsh environments. The UWB techniquesystem is innovatively incorporated into the AVs navigation system to extendextent the absolute positioning indoorsinto indoor environments. The stereo cameras are utilized to improve positioning continuity and enhance GNSS/UWB usability in outdoor-indoor obscured environments.The visual-inertial-odometry is utilized to enhance the positioning performance in the outdoor-indoor obscured environments. The proposed algorithm is evaluated over a real-world datasetsdataset in complex seamless environments. The results show that the proposed algorithm achieves 0.411m and 0.077m horizontal positioning accuracy in obscured outdoor and indoor environments, yielding 71.2 \% and 18.1 \% improvements compared with the traditional LC integration schemes, respectively. The results show that the incorporation of UWB can instantaneously correct the drifts of VIO in unknown indoor environments. The proposed TC integration algorithm achieves 71.2 \% and 18.1 \% improvements of horizontal positioning in outdoor and indoor tests, compared with the traditional LC integration, respectively. |
doi_str_mv | 10.1109/TITS.2023.3314836 |
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To achieve the fully automated operation for AVs, one important prerequisite is the accurate and reliable seamless localization covering complex outdoor-indoor scenarios. Although many solutions have been proposed to support AV localization, it is still challenging inon achieving reliableglobally drift-free positioning in seamless urbanthe unknown outdoor-indoor environments. With the current on-board sensors such as( GNSS, IMU, LiDAR, and cameras, etc.), it is difficult for AVs to achieve accurate drift-free indoor positioning and smooth indoor-outdoor transition due to the lack of GNSS indoorssignals in indoor environments. Meanwhile, challenges remain in reliable navigation under obscured conditions. In this paper, we propose a tightly coupled integration algorithm of GNSS RTK, Ultra-Wide Band (UWB) and Visual Inertial Odometry (VIO) to enhance the accuracy and reliability for AVs seamless localization in challengingharsh environments. The UWB techniquesystem is innovatively incorporated into the AVs navigation system to extendextent the absolute positioning indoorsinto indoor environments. The stereo cameras are utilized to improve positioning continuity and enhance GNSS/UWB usability in outdoor-indoor obscured environments.The visual-inertial-odometry is utilized to enhance the positioning performance in the outdoor-indoor obscured environments. The proposed algorithm is evaluated over a real-world datasetsdataset in complex seamless environments. The results show that the proposed algorithm achieves 0.411m and 0.077m horizontal positioning accuracy in obscured outdoor and indoor environments, yielding 71.2<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> and 18.1<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> improvements compared with the traditional LC integration schemes, respectively. The results show that the incorporation of UWB can instantaneously correct the drifts of VIO in unknown indoor environments. The proposed TC integration algorithm achieves 71.2<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> and 18.1<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> improvements of horizontal positioning in outdoor and indoor tests, compared with the traditional LC integration, respectively.]]></description><identifier>ISSN: 1524-9050</identifier><identifier>EISSN: 1558-0016</identifier><identifier>DOI: 10.1109/TITS.2023.3314836</identifier><identifier>CODEN: ITISFG</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Cameras ; Drift ; Global navigation satellite system ; GNSS RTK ; Indoor environments ; Intelligent transportation systems ; Localization ; Location awareness ; Navigation ; Navigation systems ; Reliability ; seamless localization ; Sensors ; tightly coupled integration ; Urban environments ; Usability ; UWB ; VIO</subject><ispartof>IEEE transactions on intelligent transportation systems, 2024-02, Vol.25 (2), p.1-13</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c294t-97805e0f2caf5c0b4e4f8a6dd481a6d511a9078d23146d0e6cc39edcfac44ef33</citedby><cites>FETCH-LOGICAL-c294t-97805e0f2caf5c0b4e4f8a6dd481a6d511a9078d23146d0e6cc39edcfac44ef33</cites><orcidid>0000-0001-7663-7743 ; 0000-0002-9553-4106 ; 0000-0003-4525-5878 ; 0000-0002-1787-5191 ; 0000-0002-9948-1347</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10260266$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10260266$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Liu, Tianxia</creatorcontrib><creatorcontrib>Li, Bofeng</creatorcontrib><creatorcontrib>Guang'e Chen</creatorcontrib><creatorcontrib>Yang, Ling</creatorcontrib><creatorcontrib>Qiao, Jing</creatorcontrib><creatorcontrib>Chen, Wu</creatorcontrib><title>Tightly Coupled Integration of GNSS/UWB/VIO for Reliable and Seamless Positioning</title><title>IEEE transactions on intelligent transportation systems</title><addtitle>TITS</addtitle><description><![CDATA[The technology of autonomous vehicle (AV) is critical in nowadays Intelligent Transportation Systems. To achieve the fully automated operation for AVs, one important prerequisite is the accurate and reliable seamless localization covering complex outdoor-indoor scenarios. Although many solutions have been proposed to support AV localization, it is still challenging inon achieving reliableglobally drift-free positioning in seamless urbanthe unknown outdoor-indoor environments. With the current on-board sensors such as( GNSS, IMU, LiDAR, and cameras, etc.), it is difficult for AVs to achieve accurate drift-free indoor positioning and smooth indoor-outdoor transition due to the lack of GNSS indoorssignals in indoor environments. Meanwhile, challenges remain in reliable navigation under obscured conditions. In this paper, we propose a tightly coupled integration algorithm of GNSS RTK, Ultra-Wide Band (UWB) and Visual Inertial Odometry (VIO) to enhance the accuracy and reliability for AVs seamless localization in challengingharsh environments. The UWB techniquesystem is innovatively incorporated into the AVs navigation system to extendextent the absolute positioning indoorsinto indoor environments. The stereo cameras are utilized to improve positioning continuity and enhance GNSS/UWB usability in outdoor-indoor obscured environments.The visual-inertial-odometry is utilized to enhance the positioning performance in the outdoor-indoor obscured environments. The proposed algorithm is evaluated over a real-world datasetsdataset in complex seamless environments. The results show that the proposed algorithm achieves 0.411m and 0.077m horizontal positioning accuracy in obscured outdoor and indoor environments, yielding 71.2<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> and 18.1<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> improvements compared with the traditional LC integration schemes, respectively. The results show that the incorporation of UWB can instantaneously correct the drifts of VIO in unknown indoor environments. The proposed TC integration algorithm achieves 71.2<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> and 18.1<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> improvements of horizontal positioning in outdoor and indoor tests, compared with the traditional LC integration, respectively.]]></description><subject>Algorithms</subject><subject>Cameras</subject><subject>Drift</subject><subject>Global navigation satellite system</subject><subject>GNSS RTK</subject><subject>Indoor environments</subject><subject>Intelligent transportation systems</subject><subject>Localization</subject><subject>Location awareness</subject><subject>Navigation</subject><subject>Navigation systems</subject><subject>Reliability</subject><subject>seamless localization</subject><subject>Sensors</subject><subject>tightly coupled integration</subject><subject>Urban environments</subject><subject>Usability</subject><subject>UWB</subject><subject>VIO</subject><issn>1524-9050</issn><issn>1558-0016</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE1Lw0AQhhdRsFZ_gOBhwXPa_Uq6OWrRGihWTavHZbuZrSkxW3fTQ_-9G9qDMDDD8L7z8SB0S8mIUpKPl8WyHDHC-IhzKiTPztCApqlMCKHZeV8zkeQkJZfoKoRt7IqU0gF6X9ab76454Knb7xqocNF2sPG6q12LncWz17Icr74ex5_FAlvn8Qc0tV43gHVb4RL0TwMh4DcX6t5St5trdGF1E-DmlIdo9fy0nL4k88WsmD7ME8Ny0SX5RJIUiGVG29SQtQBhpc6qSkgaUzxO52QiKxbfySoCmTE8h8pYbYQAy_kQ3R_n7rz73UPo1NbtfRtXKpYzyiSRgkQVPaqMdyF4sGrn6x_tD4oS1ZNTPTnVk1MnctFzd_TUAPBPz7IYGf8DKy1phw</recordid><startdate>20240201</startdate><enddate>20240201</enddate><creator>Liu, Tianxia</creator><creator>Li, Bofeng</creator><creator>Guang'e Chen</creator><creator>Yang, Ling</creator><creator>Qiao, Jing</creator><creator>Chen, Wu</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-7663-7743</orcidid><orcidid>https://orcid.org/0000-0002-9553-4106</orcidid><orcidid>https://orcid.org/0000-0003-4525-5878</orcidid><orcidid>https://orcid.org/0000-0002-1787-5191</orcidid><orcidid>https://orcid.org/0000-0002-9948-1347</orcidid></search><sort><creationdate>20240201</creationdate><title>Tightly Coupled Integration of GNSS/UWB/VIO for Reliable and Seamless Positioning</title><author>Liu, Tianxia ; Li, Bofeng ; Guang'e Chen ; Yang, Ling ; Qiao, Jing ; Chen, Wu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c294t-97805e0f2caf5c0b4e4f8a6dd481a6d511a9078d23146d0e6cc39edcfac44ef33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Cameras</topic><topic>Drift</topic><topic>Global navigation satellite system</topic><topic>GNSS RTK</topic><topic>Indoor environments</topic><topic>Intelligent transportation systems</topic><topic>Localization</topic><topic>Location awareness</topic><topic>Navigation</topic><topic>Navigation systems</topic><topic>Reliability</topic><topic>seamless localization</topic><topic>Sensors</topic><topic>tightly coupled integration</topic><topic>Urban environments</topic><topic>Usability</topic><topic>UWB</topic><topic>VIO</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Tianxia</creatorcontrib><creatorcontrib>Li, Bofeng</creatorcontrib><creatorcontrib>Guang'e Chen</creatorcontrib><creatorcontrib>Yang, Ling</creatorcontrib><creatorcontrib>Qiao, Jing</creatorcontrib><creatorcontrib>Chen, Wu</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on intelligent transportation systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Liu, Tianxia</au><au>Li, Bofeng</au><au>Guang'e Chen</au><au>Yang, Ling</au><au>Qiao, Jing</au><au>Chen, Wu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Tightly Coupled Integration of GNSS/UWB/VIO for Reliable and Seamless Positioning</atitle><jtitle>IEEE transactions on intelligent transportation systems</jtitle><stitle>TITS</stitle><date>2024-02-01</date><risdate>2024</risdate><volume>25</volume><issue>2</issue><spage>1</spage><epage>13</epage><pages>1-13</pages><issn>1524-9050</issn><eissn>1558-0016</eissn><coden>ITISFG</coden><abstract><![CDATA[The technology of autonomous vehicle (AV) is critical in nowadays Intelligent Transportation Systems. To achieve the fully automated operation for AVs, one important prerequisite is the accurate and reliable seamless localization covering complex outdoor-indoor scenarios. Although many solutions have been proposed to support AV localization, it is still challenging inon achieving reliableglobally drift-free positioning in seamless urbanthe unknown outdoor-indoor environments. With the current on-board sensors such as( GNSS, IMU, LiDAR, and cameras, etc.), it is difficult for AVs to achieve accurate drift-free indoor positioning and smooth indoor-outdoor transition due to the lack of GNSS indoorssignals in indoor environments. Meanwhile, challenges remain in reliable navigation under obscured conditions. In this paper, we propose a tightly coupled integration algorithm of GNSS RTK, Ultra-Wide Band (UWB) and Visual Inertial Odometry (VIO) to enhance the accuracy and reliability for AVs seamless localization in challengingharsh environments. The UWB techniquesystem is innovatively incorporated into the AVs navigation system to extendextent the absolute positioning indoorsinto indoor environments. The stereo cameras are utilized to improve positioning continuity and enhance GNSS/UWB usability in outdoor-indoor obscured environments.The visual-inertial-odometry is utilized to enhance the positioning performance in the outdoor-indoor obscured environments. The proposed algorithm is evaluated over a real-world datasetsdataset in complex seamless environments. The results show that the proposed algorithm achieves 0.411m and 0.077m horizontal positioning accuracy in obscured outdoor and indoor environments, yielding 71.2<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> and 18.1<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> improvements compared with the traditional LC integration schemes, respectively. The results show that the incorporation of UWB can instantaneously correct the drifts of VIO in unknown indoor environments. The proposed TC integration algorithm achieves 71.2<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> and 18.1<inline-formula> <tex-math notation="LaTeX">\%</tex-math> </inline-formula> improvements of horizontal positioning in outdoor and indoor tests, compared with the traditional LC integration, respectively.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TITS.2023.3314836</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-7663-7743</orcidid><orcidid>https://orcid.org/0000-0002-9553-4106</orcidid><orcidid>https://orcid.org/0000-0003-4525-5878</orcidid><orcidid>https://orcid.org/0000-0002-1787-5191</orcidid><orcidid>https://orcid.org/0000-0002-9948-1347</orcidid></addata></record> |
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subjects | Algorithms Cameras Drift Global navigation satellite system GNSS RTK Indoor environments Intelligent transportation systems Localization Location awareness Navigation Navigation systems Reliability seamless localization Sensors tightly coupled integration Urban environments Usability UWB VIO |
title | Tightly Coupled Integration of GNSS/UWB/VIO for Reliable and Seamless Positioning |
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