DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Yeong Sang | ko |
dc.contributor.author | Shin, Young-Sik | ko |
dc.contributor.author | Kim, Ayoung | ko |
dc.date.accessioned | 2020-12-21T09:30:11Z | - |
dc.date.available | 2020-12-21T09:30:11Z | - |
dc.date.created | 2020-11-30 | - |
dc.date.created | 2020-11-30 | - |
dc.date.issued | 2020-05-31 | - |
dc.identifier.citation | IEEE International Conference on Robotics and Automation, ICRA 2020, pp.2617 - 2623 | - |
dc.identifier.issn | 1050-4729 | - |
dc.identifier.uri | http://hdl.handle.net/10203/278855 | - |
dc.description.abstract | Recent studies in radar-based navigation present promising navigation performance using scanning radars. These scanning radar-based odometry methods are mostly feature-based; they detect and match salient features within a radar image. Differing from existing feature-based methods, this paper reports on a method using direct radar odometry, PhaRaO, which infers relative motion from a pair of radar scans via phase correlation. Specifically, we apply the Fourier Mellin transform (FMT) for Cartesian and log-polar radar images to sequentially estimate rotation and translation. In doing so, we decouple rotation and translation estimations in a coarse-to-fine manner to achieve real-time performance. The proposed method is evaluated using large-scale radar data obtained from various environments. The inferred trajectory yields a 2.34% (translation) and 2.93° (rotation) Relative Error (RE) over a 4km path length on average for the odometry estimation. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | PhaRaO: Direct Radar Odometry using Phase Correlation | - |
dc.type | Conference | - |
dc.identifier.wosid | 000712319501135 | - |
dc.identifier.scopusid | 2-s2.0-85092745896 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 2617 | - |
dc.citation.endingpage | 2623 | - |
dc.citation.publicationname | IEEE International Conference on Robotics and Automation, ICRA 2020 | - |
dc.identifier.conferencecountry | FR | - |
dc.identifier.conferencelocation | Virtual | - |
dc.identifier.doi | 10.1109/ICRA40945.2020.9197231 | - |
dc.contributor.localauthor | Kim, Ayoung | - |
dc.contributor.nonIdAuthor | Park, Yeong Sang | - |
dc.contributor.nonIdAuthor | Shin, Young-Sik | - |
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