Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles
IEEE Robotics and Automation Letters ( Volume: 4 , Issue: 2 , April 2019 ) Today, rail vehicle localization is based on infrastructure-side Balises (beacons) together with on-board odometry to determine whether a rail segment is occupied. Such a coarse locking leads to a sub-optimal usage of the rai...
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| creator | Tschopp, Florian Schneider, Thomas Palmer, Andrew W Nourani-Vatani, Navid Cadena, Cesar Siegwart, Roland Nieto, Juan |
| description | IEEE Robotics and Automation Letters ( Volume: 4 , Issue: 2 ,
April 2019 ) Today, rail vehicle localization is based on infrastructure-side Balises
(beacons) together with on-board odometry to determine whether a rail segment
is occupied. Such a coarse locking leads to a sub-optimal usage of the rail
networks. New railway standards propose the use of moving blocks centered
around the rail vehicles to increase the capacity of the network. However, this
approach requires accurate and robust position and velocity estimation of all
vehicles. In this work, we investigate the applicability, challenges and
limitations of current visual and visual-inertial motion estimation frameworks
for rail applications. An evaluation against RTK-GPS ground truth is performed
on multiple datasets recorded in industrial, sub-urban, and forest
environments. Our results show that stereo visual-inertial odometry has a great
potential to provide a precise motion estimation because of its complementing
sensor modalities and shows superior performance in challenging situations
compared to other frameworks. |
| doi_str_mv | 10.48550/arxiv.1904.00936 |
| format | Article |
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April 2019 ) Today, rail vehicle localization is based on infrastructure-side Balises
(beacons) together with on-board odometry to determine whether a rail segment
is occupied. Such a coarse locking leads to a sub-optimal usage of the rail
networks. New railway standards propose the use of moving blocks centered
around the rail vehicles to increase the capacity of the network. However, this
approach requires accurate and robust position and velocity estimation of all
vehicles. In this work, we investigate the applicability, challenges and
limitations of current visual and visual-inertial motion estimation frameworks
for rail applications. An evaluation against RTK-GPS ground truth is performed
on multiple datasets recorded in industrial, sub-urban, and forest
environments. Our results show that stereo visual-inertial odometry has a great
potential to provide a precise motion estimation because of its complementing
sensor modalities and shows superior performance in challenging situations
compared to other frameworks.</description><identifier>DOI: 10.48550/arxiv.1904.00936</identifier><language>eng</language><subject>Computer Science - Robotics</subject><creationdate>2019-04</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1904.00936$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1904.00936$$DView paper in arXiv$$Hfree_for_read</backlink><backlink>$$Uhttps://doi.org/10.1109/LRA.2019.2897169$$DView published paper (Access to full text may be restricted)$$Hfree_for_read</backlink></links><search><creatorcontrib>Tschopp, Florian</creatorcontrib><creatorcontrib>Schneider, Thomas</creatorcontrib><creatorcontrib>Palmer, Andrew W</creatorcontrib><creatorcontrib>Nourani-Vatani, Navid</creatorcontrib><creatorcontrib>Cadena, Cesar</creatorcontrib><creatorcontrib>Siegwart, Roland</creatorcontrib><creatorcontrib>Nieto, Juan</creatorcontrib><title>Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles</title><description>IEEE Robotics and Automation Letters ( Volume: 4 , Issue: 2 ,
April 2019 ) Today, rail vehicle localization is based on infrastructure-side Balises
(beacons) together with on-board odometry to determine whether a rail segment
is occupied. Such a coarse locking leads to a sub-optimal usage of the rail
networks. New railway standards propose the use of moving blocks centered
around the rail vehicles to increase the capacity of the network. However, this
approach requires accurate and robust position and velocity estimation of all
vehicles. In this work, we investigate the applicability, challenges and
limitations of current visual and visual-inertial motion estimation frameworks
for rail applications. An evaluation against RTK-GPS ground truth is performed
on multiple datasets recorded in industrial, sub-urban, and forest
environments. Our results show that stereo visual-inertial odometry has a great
potential to provide a precise motion estimation because of its complementing
sensor modalities and shows superior performance in challenging situations
compared to other frameworks.</description><subject>Computer Science - Robotics</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNpjYJA0NNAzsTA1NdBPLKrILNMztDQw0TMwsDQ242Twcq0oSC3KzE3NK0nMUXDOzy1ILMoszs9TyE9TCMssLk3M0XXMTElNUfBPyc9NLSmqVPBNLcnITylWSMsvUghKzMxRCEvNyEzOSS3mYWBNS8wpTuWF0twM8m6uIc4eumBb4wuAtiQWVcaDbI8H225MWAUAd7A6XQ</recordid><startdate>20190401</startdate><enddate>20190401</enddate><creator>Tschopp, Florian</creator><creator>Schneider, Thomas</creator><creator>Palmer, Andrew W</creator><creator>Nourani-Vatani, Navid</creator><creator>Cadena, Cesar</creator><creator>Siegwart, Roland</creator><creator>Nieto, Juan</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20190401</creationdate><title>Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles</title><author>Tschopp, Florian ; Schneider, Thomas ; Palmer, Andrew W ; Nourani-Vatani, Navid ; Cadena, Cesar ; Siegwart, Roland ; Nieto, Juan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_1904_009363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Computer Science - Robotics</topic><toplevel>online_resources</toplevel><creatorcontrib>Tschopp, Florian</creatorcontrib><creatorcontrib>Schneider, Thomas</creatorcontrib><creatorcontrib>Palmer, Andrew W</creatorcontrib><creatorcontrib>Nourani-Vatani, Navid</creatorcontrib><creatorcontrib>Cadena, Cesar</creatorcontrib><creatorcontrib>Siegwart, Roland</creatorcontrib><creatorcontrib>Nieto, Juan</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tschopp, Florian</au><au>Schneider, Thomas</au><au>Palmer, Andrew W</au><au>Nourani-Vatani, Navid</au><au>Cadena, Cesar</au><au>Siegwart, Roland</au><au>Nieto, Juan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles</atitle><date>2019-04-01</date><risdate>2019</risdate><abstract>IEEE Robotics and Automation Letters ( Volume: 4 , Issue: 2 ,
April 2019 ) Today, rail vehicle localization is based on infrastructure-side Balises
(beacons) together with on-board odometry to determine whether a rail segment
is occupied. Such a coarse locking leads to a sub-optimal usage of the rail
networks. New railway standards propose the use of moving blocks centered
around the rail vehicles to increase the capacity of the network. However, this
approach requires accurate and robust position and velocity estimation of all
vehicles. In this work, we investigate the applicability, challenges and
limitations of current visual and visual-inertial motion estimation frameworks
for rail applications. An evaluation against RTK-GPS ground truth is performed
on multiple datasets recorded in industrial, sub-urban, and forest
environments. Our results show that stereo visual-inertial odometry has a great
potential to provide a precise motion estimation because of its complementing
sensor modalities and shows superior performance in challenging situations
compared to other frameworks.</abstract><doi>10.48550/arxiv.1904.00936</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Robotics |
| title | Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles |
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