Matches in SemOpenAlex for { <https://semopenalex.org/work/W2020120750> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W2020120750 abstract "The SLAM or localization needs successful data association of the detected feature with landmarks. Well described features of the environment are essential for good data association. In this paper, the localization of the robot is executed by the extended Kalman filter (EKF) with given minimum landmarks of the environment. Consistent features for localization are extracted by using only sparse sonar data. Features are extracted by using a sonar data clustering from a footprint-association (FPA) method and a feature fitting from a least squares (LS) method to overcome challenges associated with sonar sensors, such as a wide beam aperture and a specular reflection effect. The extracted features are, also, evaluated as a post-processing through the probabilistic association which associates the extracted feature with the weighted average probability of the grids that are located within the area of position uncertainty of the feature. The proposed methods have been tested in a real home environment with a mobile robot" @default.
- W2020120750 created "2016-06-24" @default.
- W2020120750 creator A5013808012 @default.
- W2020120750 creator A5023838707 @default.
- W2020120750 creator A5035674745 @default.
- W2020120750 date "2006-01-01" @default.
- W2020120750 modified "2023-09-27" @default.
- W2020120750 title "EKF Localization and Mapping by Using Consistent Sonar Feature with Given Minimum Landmarks" @default.
- W2020120750 cites W1652749684 @default.
- W2020120750 cites W1656165940 @default.
- W2020120750 cites W1960697044 @default.
- W2020120750 cites W1981056846 @default.
- W2020120750 cites W2013097588 @default.
- W2020120750 cites W2018153268 @default.
- W2020120750 cites W2080692320 @default.
- W2020120750 cites W2081486739 @default.
- W2020120750 cites W2085261163 @default.
- W2020120750 cites W2093425426 @default.
- W2020120750 cites W2099034771 @default.
- W2020120750 cites W2108569360 @default.
- W2020120750 cites W2109513571 @default.
- W2020120750 cites W2154418813 @default.
- W2020120750 cites W2161434168 @default.
- W2020120750 cites W2202305162 @default.
- W2020120750 cites W2740373864 @default.
- W2020120750 cites W2810650918 @default.
- W2020120750 doi "https://doi.org/10.1109/sice.2006.314956" @default.
- W2020120750 hasPublicationYear "2006" @default.
- W2020120750 type Work @default.
- W2020120750 sameAs 2020120750 @default.
- W2020120750 citedByCount "2" @default.
- W2020120750 crossrefType "proceedings-article" @default.
- W2020120750 hasAuthorship W2020120750A5013808012 @default.
- W2020120750 hasAuthorship W2020120750A5023838707 @default.
- W2020120750 hasAuthorship W2020120750A5035674745 @default.
- W2020120750 hasConcept C138885662 @default.
- W2020120750 hasConcept C153180895 @default.
- W2020120750 hasConcept C154945302 @default.
- W2020120750 hasConcept C157286648 @default.
- W2020120750 hasConcept C181255713 @default.
- W2020120750 hasConcept C19966478 @default.
- W2020120750 hasConcept C206833254 @default.
- W2020120750 hasConcept C2776401178 @default.
- W2020120750 hasConcept C31972630 @default.
- W2020120750 hasConcept C41008148 @default.
- W2020120750 hasConcept C41895202 @default.
- W2020120750 hasConcept C555745239 @default.
- W2020120750 hasConcept C86369673 @default.
- W2020120750 hasConcept C90509273 @default.
- W2020120750 hasConceptScore W2020120750C138885662 @default.
- W2020120750 hasConceptScore W2020120750C153180895 @default.
- W2020120750 hasConceptScore W2020120750C154945302 @default.
- W2020120750 hasConceptScore W2020120750C157286648 @default.
- W2020120750 hasConceptScore W2020120750C181255713 @default.
- W2020120750 hasConceptScore W2020120750C19966478 @default.
- W2020120750 hasConceptScore W2020120750C206833254 @default.
- W2020120750 hasConceptScore W2020120750C2776401178 @default.
- W2020120750 hasConceptScore W2020120750C31972630 @default.
- W2020120750 hasConceptScore W2020120750C41008148 @default.
- W2020120750 hasConceptScore W2020120750C41895202 @default.
- W2020120750 hasConceptScore W2020120750C555745239 @default.
- W2020120750 hasConceptScore W2020120750C86369673 @default.
- W2020120750 hasConceptScore W2020120750C90509273 @default.
- W2020120750 hasLocation W20201207501 @default.
- W2020120750 hasOpenAccess W2020120750 @default.
- W2020120750 hasPrimaryLocation W20201207501 @default.
- W2020120750 hasRelatedWork W1485534706 @default.
- W2020120750 hasRelatedWork W1506187828 @default.
- W2020120750 hasRelatedWork W1892275345 @default.
- W2020120750 hasRelatedWork W2019203251 @default.
- W2020120750 hasRelatedWork W2116298349 @default.
- W2020120750 hasRelatedWork W2163622079 @default.
- W2020120750 hasRelatedWork W2542963140 @default.
- W2020120750 hasRelatedWork W2554592351 @default.
- W2020120750 hasRelatedWork W3153627202 @default.
- W2020120750 hasRelatedWork W4206483957 @default.
- W2020120750 isParatext "false" @default.
- W2020120750 isRetracted "false" @default.
- W2020120750 magId "2020120750" @default.
- W2020120750 workType "article" @default.