Localization of an unmanned ground vehicle using 3D registration of laser range data and DSM
Localization of an unmanned ground vehicle (UGV) is a very important task for autonomous vehicle navigation. In this paper, we propose a computer vision technique to identify the location of an outdoor UGV. The proposed technique is based on 3D registration of 360 degree laser range data to a digita...
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creator | Soon-Yong Park Sung-In Choi Jaekyoung Moon Joon Kim Yong Woon Park |
description | Localization of an unmanned ground vehicle (UGV) is a very important task for autonomous vehicle navigation. In this paper, we propose a computer vision technique to identify the location of an outdoor UGV. The proposed technique is based on 3D registration of 360 degree laser range data to a digital surface model (DSM). A long sequence of range frames is obtained from a rotating range sensor which is mounted on the top of the vehicle. Two novel approaches are proposed for accurate 3D registration of range data and the DSM. First, registration is done between range frames in a pair-wise manner followed by a refinement with the DSM. Second, we divide the DSM to several layers and find correspondences near the current vehicle elevation. This reduces the number of outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on four outdoor paths is presented with respect to ground truth. |
doi_str_mv | 10.1109/WACV.2009.5403059 |
format | Conference Proceeding |
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In this paper, we propose a computer vision technique to identify the location of an outdoor UGV. The proposed technique is based on 3D registration of 360 degree laser range data to a digital surface model (DSM). A long sequence of range frames is obtained from a rotating range sensor which is mounted on the top of the vehicle. Two novel approaches are proposed for accurate 3D registration of range data and the DSM. First, registration is done between range frames in a pair-wise manner followed by a refinement with the DSM. Second, we divide the DSM to several layers and find correspondences near the current vehicle elevation. This reduces the number of outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. 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In this paper, we propose a computer vision technique to identify the location of an outdoor UGV. The proposed technique is based on 3D registration of 360 degree laser range data to a digital surface model (DSM). A long sequence of range frames is obtained from a rotating range sensor which is mounted on the top of the vehicle. Two novel approaches are proposed for accurate 3D registration of range data and the DSM. First, registration is done between range frames in a pair-wise manner followed by a refinement with the DSM. Second, we divide the DSM to several layers and find correspondences near the current vehicle elevation. This reduces the number of outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on four outdoor paths is presented with respect to ground truth.</description><subject>Iterative algorithms</subject><subject>Iterative closest point algorithm</subject><subject>Land vehicles</subject><subject>Laser modes</subject><subject>Mobile robots</subject><subject>Navigation</subject><subject>Remotely operated vehicles</subject><subject>Road vehicles</subject><subject>Surface emitting lasers</subject><subject>Vehicle driving</subject><issn>1550-5790</issn><issn>2642-9381</issn><isbn>9781424454976</isbn><isbn>1424454972</isbn><isbn>1424454980</isbn><isbn>9781424454983</isbn><isbn>9781424454969</isbn><isbn>1424454964</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9kMtOwzAURM1LopR8AGLjH0i4fiX2smp5SUEsimCDVLnxdTBKHeSkSPD1VKIwm1kczVkMIRcMCsbAXL3M5s8FBzCFkiBAmQNyxiSXUkmj4ZBMeCl5boRmRyQzlf5jVXlMJkwpyFVl4JRkw_AOu0jFBYMJea37xnbh246hj7T31Ea6jRsbIzrapn4bHf3Et9B0SLdDiC0VC5qwDcOY_jedHTDRZGOL1NnR7iSOLpYP5-TE227AbN9Tsry5fprf5fXj7f18VufBwJh7bbgXDTjuyzVq7rRVqD1o70vwqmLeKsXXDVbNukSutXam4TuCWhpuxZRc_loDIq4-UtjY9LXa3yR-AK4ZV9M</recordid><startdate>200912</startdate><enddate>200912</enddate><creator>Soon-Yong Park</creator><creator>Sung-In Choi</creator><creator>Jaekyoung Moon</creator><creator>Joon Kim</creator><creator>Yong Woon Park</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200912</creationdate><title>Localization of an unmanned ground vehicle using 3D registration of laser range data and DSM</title><author>Soon-Yong Park ; Sung-In Choi ; Jaekyoung Moon ; Joon Kim ; Yong Woon Park</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-f892f3c0d2f6be82d8a5e8f08ff60f571fa552bce7cb6e2888d9c20f5e8492a3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Iterative algorithms</topic><topic>Iterative closest point algorithm</topic><topic>Land vehicles</topic><topic>Laser modes</topic><topic>Mobile robots</topic><topic>Navigation</topic><topic>Remotely operated vehicles</topic><topic>Road vehicles</topic><topic>Surface emitting lasers</topic><topic>Vehicle driving</topic><toplevel>online_resources</toplevel><creatorcontrib>Soon-Yong Park</creatorcontrib><creatorcontrib>Sung-In Choi</creatorcontrib><creatorcontrib>Jaekyoung Moon</creatorcontrib><creatorcontrib>Joon Kim</creatorcontrib><creatorcontrib>Yong Woon Park</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Soon-Yong Park</au><au>Sung-In Choi</au><au>Jaekyoung Moon</au><au>Joon Kim</au><au>Yong Woon Park</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Localization of an unmanned ground vehicle using 3D registration of laser range data and DSM</atitle><btitle>2009 Workshop on Applications of Computer Vision (WACV)</btitle><stitle>WACV</stitle><date>2009-12</date><risdate>2009</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>1550-5790</issn><eissn>2642-9381</eissn><isbn>9781424454976</isbn><isbn>1424454972</isbn><eisbn>1424454980</eisbn><eisbn>9781424454983</eisbn><eisbn>9781424454969</eisbn><eisbn>1424454964</eisbn><abstract>Localization of an unmanned ground vehicle (UGV) is a very important task for autonomous vehicle navigation. In this paper, we propose a computer vision technique to identify the location of an outdoor UGV. The proposed technique is based on 3D registration of 360 degree laser range data to a digital surface model (DSM). A long sequence of range frames is obtained from a rotating range sensor which is mounted on the top of the vehicle. Two novel approaches are proposed for accurate 3D registration of range data and the DSM. First, registration is done between range frames in a pair-wise manner followed by a refinement with the DSM. Second, we divide the DSM to several layers and find correspondences near the current vehicle elevation. This reduces the number of outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. 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ispartof | 2009 Workshop on Applications of Computer Vision (WACV), 2009, p.1-6 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Iterative algorithms Iterative closest point algorithm Land vehicles Laser modes Mobile robots Navigation Remotely operated vehicles Road vehicles Surface emitting lasers Vehicle driving |
title | Localization of an unmanned ground vehicle using 3D registration of laser range data and DSM |
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