DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Sungho | ko |
dc.contributor.author | Kweon, In-So | ko |
dc.date.accessioned | 2019-04-15T15:30:59Z | - |
dc.date.available | 2019-04-15T15:30:59Z | - |
dc.date.created | 2013-10-10 | - |
dc.date.issued | 2013-05 | - |
dc.identifier.citation | Lecture Notes in Electrical Engineering, v.240, pp.975 - 981 | - |
dc.identifier.issn | 1876-1100 | - |
dc.identifier.uri | http://hdl.handle.net/10203/255014 | - |
dc.description.abstract | This paper presents a novel paradigm of a global localization method motivated. The proposed localization paradigm consists of three parts: panoramic image acquisition, multiple object recognition, and grid-based localization. Multiple object recognition information from panoramic images is utilized in the localization part. High level object information is useful not only for global localization but also robot-object interaction. The metric global localization (position, viewing direction) is conducted based on the bearing information of recognized objects from just one panoramic image. The experimental results validate the feasibility of the novel localization paradigm. | - |
dc.language | English | - |
dc.publisher | Springer | - |
dc.title | Omnidirectional Object Recognition Based Mobile Robot Localization | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 240 | - |
dc.citation.beginningpage | 975 | - |
dc.citation.endingpage | 981 | - |
dc.citation.publicationname | Lecture Notes in Electrical Engineering | - |
dc.identifier.doi | 10.1007/978-94-007-6738-6_120 | - |
dc.contributor.localauthor | Kweon, In-So | - |
dc.contributor.nonIdAuthor | Kim, Sungho | - |
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