Matches in SemOpenAlex for { <https://semopenalex.org/work/W2938314191> ?p ?o ?g. }
Showing items 1 to 81 of
81
with 100 items per page.
- W2938314191 abstract "Considering the structural similarity of environments, an image-sequence-based mobile robot localization algorithm is proposed, which utilizes image sequences to represent different places in environments. To achieve localization of the mobile robot, the mobile robot is allowed to explore the environments in advance. The RGB image data stream acquired by the mobile robot is partitioned into different image sequences according to the moving distance of the mobile robot. Then, each of image sequences is sent into an LSTM (Long Short-Term Memory)network to learn the characteristics of each image sequence. The final cell states of the LSTM will be treated as the features of the image sequence. When the mobile robot travels in the environments once again, the newly acquired image sequence will be sent into this well-trained LSTM network to extract the features of the image sequence. By matching features among different image sequences, the mobile robot can recognize which place it may locate in. Finally, experimental comparisons with single-frame-based localization algorithms are conducted to verify the performance of the proposed algorithm from the localization accuracy." @default.
- W2938314191 created "2019-04-25" @default.
- W2938314191 creator A5023827162 @default.
- W2938314191 creator A5037573848 @default.
- W2938314191 creator A5041723650 @default.
- W2938314191 creator A5042534349 @default.
- W2938314191 creator A5084899203 @default.
- W2938314191 date "2018-07-01" @default.
- W2938314191 modified "2023-09-27" @default.
- W2938314191 title "Image-Sequence-Based Mobile Robot Localization" @default.
- W2938314191 cites W1566135517 @default.
- W2938314191 cites W1632335209 @default.
- W2938314191 cites W1650079892 @default.
- W2938314191 cites W1923390179 @default.
- W2938314191 cites W1974093076 @default.
- W2938314191 cites W2002819613 @default.
- W2938314191 cites W2005389775 @default.
- W2938314191 cites W2064675550 @default.
- W2938314191 cites W2088781837 @default.
- W2938314191 cites W2132311402 @default.
- W2938314191 cites W2132395595 @default.
- W2938314191 cites W2144824356 @default.
- W2938314191 cites W2160142779 @default.
- W2938314191 cites W2523916032 @default.
- W2938314191 cites W2560863959 @default.
- W2938314191 cites W2562131404 @default.
- W2938314191 cites W2606189077 @default.
- W2938314191 cites W2737223639 @default.
- W2938314191 cites W2181410459 @default.
- W2938314191 doi "https://doi.org/10.1109/cyber.2018.8688088" @default.
- W2938314191 hasPublicationYear "2018" @default.
- W2938314191 type Work @default.
- W2938314191 sameAs 2938314191 @default.
- W2938314191 citedByCount "0" @default.
- W2938314191 crossrefType "proceedings-article" @default.
- W2938314191 hasAuthorship W2938314191A5023827162 @default.
- W2938314191 hasAuthorship W2938314191A5037573848 @default.
- W2938314191 hasAuthorship W2938314191A5041723650 @default.
- W2938314191 hasAuthorship W2938314191A5042534349 @default.
- W2938314191 hasAuthorship W2938314191A5084899203 @default.
- W2938314191 hasConcept C103278499 @default.
- W2938314191 hasConcept C115961682 @default.
- W2938314191 hasConcept C126042441 @default.
- W2938314191 hasConcept C154945302 @default.
- W2938314191 hasConcept C19966478 @default.
- W2938314191 hasConcept C2778112365 @default.
- W2938314191 hasConcept C31972630 @default.
- W2938314191 hasConcept C41008148 @default.
- W2938314191 hasConcept C54355233 @default.
- W2938314191 hasConcept C76155785 @default.
- W2938314191 hasConcept C86803240 @default.
- W2938314191 hasConcept C90509273 @default.
- W2938314191 hasConceptScore W2938314191C103278499 @default.
- W2938314191 hasConceptScore W2938314191C115961682 @default.
- W2938314191 hasConceptScore W2938314191C126042441 @default.
- W2938314191 hasConceptScore W2938314191C154945302 @default.
- W2938314191 hasConceptScore W2938314191C19966478 @default.
- W2938314191 hasConceptScore W2938314191C2778112365 @default.
- W2938314191 hasConceptScore W2938314191C31972630 @default.
- W2938314191 hasConceptScore W2938314191C41008148 @default.
- W2938314191 hasConceptScore W2938314191C54355233 @default.
- W2938314191 hasConceptScore W2938314191C76155785 @default.
- W2938314191 hasConceptScore W2938314191C86803240 @default.
- W2938314191 hasConceptScore W2938314191C90509273 @default.
- W2938314191 hasLocation W29383141911 @default.
- W2938314191 hasOpenAccess W2938314191 @default.
- W2938314191 hasPrimaryLocation W29383141911 @default.
- W2938314191 hasRelatedWork W1482783011 @default.
- W2938314191 hasRelatedWork W1516311991 @default.
- W2938314191 hasRelatedWork W2070325379 @default.
- W2938314191 hasRelatedWork W2077116599 @default.
- W2938314191 hasRelatedWork W2096142835 @default.
- W2938314191 hasRelatedWork W2147087847 @default.
- W2938314191 hasRelatedWork W2164688428 @default.
- W2938314191 hasRelatedWork W2269820139 @default.
- W2938314191 hasRelatedWork W2386868913 @default.
- W2938314191 hasRelatedWork W2162526407 @default.
- W2938314191 isParatext "false" @default.
- W2938314191 isRetracted "false" @default.
- W2938314191 magId "2938314191" @default.
- W2938314191 workType "article" @default.