Performance Improvement of Iterative Closest Point-Based Outdoor SLAM by Rotation Invariant Descriptors of Salient Regions
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Yong-Ju | - |
dc.contributor.author | Song, Jae-Bok | - |
dc.contributor.author | Choi, Ji-Hoon | - |
dc.date.accessioned | 2021-09-05T22:01:18Z | - |
dc.date.available | 2021-09-05T22:01:18Z | - |
dc.date.created | 2021-06-14 | - |
dc.date.issued | 2013-09 | - |
dc.identifier.issn | 0921-0296 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/102235 | - |
dc.description.abstract | To navigate in an unknown environment, a robot should build a model for the environment. For outdoor environments, a three-dimensional (3-D) map is usually used as a main model. This study considers outdoor simultaneous localization and mapping (SLAM) to build a global 3-D map by matching local 3-D maps. An iterative closest point (ICP) algorithm is used to match local 3-D maps and estimate a robot pose, but an alignment error is generated by the ICP algorithm due to the false selection of corresponding points. We propose a new method to extract 3-D points that are valid for ICP matching. Rotation-invariant descriptors are introduced for robust correspondence. 3-D environmental data acquired by tilting a 2-D laser scanner are used to build local 3-D maps. Experimental results in real environments show the increased accuracy of the ICP-based matching and a reduction in matching time. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER | - |
dc.subject | REGISTRATION | - |
dc.subject | VISION | - |
dc.title | Performance Improvement of Iterative Closest Point-Based Outdoor SLAM by Rotation Invariant Descriptors of Salient Regions | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Song, Jae-Bok | - |
dc.identifier.doi | 10.1007/s10846-012-9786-2 | - |
dc.identifier.scopusid | 2-s2.0-84883134659 | - |
dc.identifier.wosid | 000322882100006 | - |
dc.identifier.bibliographicCitation | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, v.71, no.3-4, pp.349 - 360 | - |
dc.relation.isPartOf | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | - |
dc.citation.title | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | - |
dc.citation.volume | 71 | - |
dc.citation.number | 3-4 | - |
dc.citation.startPage | 349 | - |
dc.citation.endPage | 360 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Robotics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Robotics | - |
dc.subject.keywordPlus | REGISTRATION | - |
dc.subject.keywordPlus | VISION | - |
dc.subject.keywordAuthor | Mapping | - |
dc.subject.keywordAuthor | SLAM | - |
dc.subject.keywordAuthor | Iterative closest point (ICP) | - |
dc.subject.keywordAuthor | 3-D maps | - |
dc.subject.keywordAuthor | Outdoor navigation | - |
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