Matches in SemOpenAlex for { <https://semopenalex.org/work/W2003228681> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W2003228681 endingPage "2387" @default.
- W2003228681 startingPage "2376" @default.
- W2003228681 abstract "In this paper, a decentralized platform for simultaneous localization and mapping (SLAM) with multiple robots is developed. Each robot performs single robot view-based SLAM using an extended Kalman filter to fuse data from two encoders and a laser ranger. To extend this approach to multiple robot SLAM, a novel occupancy grid map fusion algorithm is proposed. Map fusion is achieved through a multistep process that includes image preprocessing, map learning (clustering) using neural networks, relative orientation extraction using norm histogram cross correlation and a Radon transform, relative translation extraction using matching norm vectors, and then verification of the results. The proposed map learning method is a process based on the self-organizing map. In the learning phase, the obstacles of the map are learned by clustering the occupied cells of the map into clusters. The learning is an unsupervised process which can be done on the fly without any need to have output training patterns. The clusters represent the spatial form of the map and make further analyses of the map easier and faster. Also, clusters can be interpreted as features extracted from the occupancy grid map so the map fusion problem becomes a task of matching features. Results of the experiments from tests performed on a real environment with multiple robots prove the effectiveness of the proposed solution." @default.
- W2003228681 created "2016-06-24" @default.
- W2003228681 creator A5037065865 @default.
- W2003228681 creator A5047941621 @default.
- W2003228681 creator A5067137977 @default.
- W2003228681 creator A5089481314 @default.
- W2003228681 date "2011-12-01" @default.
- W2003228681 modified "2023-10-17" @default.
- W2003228681 title "Neural Network-Based Multiple Robot Simultaneous Localization and Mapping" @default.
- W2003228681 cites W1522183152 @default.
- W2003228681 cites W1584640914 @default.
- W2003228681 cites W1656165940 @default.
- W2003228681 cites W1976809435 @default.
- W2003228681 cites W2006548260 @default.
- W2003228681 cites W2029724021 @default.
- W2003228681 cites W2035360823 @default.
- W2003228681 cites W2068685220 @default.
- W2003228681 cites W2089441731 @default.
- W2003228681 cites W2104502110 @default.
- W2003228681 cites W2127578024 @default.
- W2003228681 cites W2133846307 @default.
- W2003228681 cites W2135187880 @default.
- W2003228681 cites W2154319942 @default.
- W2003228681 cites W2155377758 @default.
- W2003228681 cites W2156229246 @default.
- W2003228681 cites W2170229019 @default.
- W2003228681 cites W2171209182 @default.
- W2003228681 doi "https://doi.org/10.1109/tnn.2011.2176541" @default.
- W2003228681 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/22156983" @default.
- W2003228681 hasPublicationYear "2011" @default.
- W2003228681 type Work @default.
- W2003228681 sameAs 2003228681 @default.
- W2003228681 citedByCount "53" @default.
- W2003228681 countsByYear W20032286812012 @default.
- W2003228681 countsByYear W20032286812013 @default.
- W2003228681 countsByYear W20032286812014 @default.
- W2003228681 countsByYear W20032286812015 @default.
- W2003228681 countsByYear W20032286812016 @default.
- W2003228681 countsByYear W20032286812017 @default.
- W2003228681 countsByYear W20032286812018 @default.
- W2003228681 countsByYear W20032286812019 @default.
- W2003228681 countsByYear W20032286812020 @default.
- W2003228681 countsByYear W20032286812021 @default.
- W2003228681 countsByYear W20032286812022 @default.
- W2003228681 countsByYear W20032286812023 @default.
- W2003228681 crossrefType "journal-article" @default.
- W2003228681 hasAuthorship W2003228681A5037065865 @default.
- W2003228681 hasAuthorship W2003228681A5047941621 @default.
- W2003228681 hasAuthorship W2003228681A5067137977 @default.
- W2003228681 hasAuthorship W2003228681A5089481314 @default.
- W2003228681 hasConcept C111168008 @default.
- W2003228681 hasConcept C153180895 @default.
- W2003228681 hasConcept C154945302 @default.
- W2003228681 hasConcept C19966478 @default.
- W2003228681 hasConcept C31972630 @default.
- W2003228681 hasConcept C41008148 @default.
- W2003228681 hasConcept C57077369 @default.
- W2003228681 hasConcept C73555534 @default.
- W2003228681 hasConcept C86369673 @default.
- W2003228681 hasConcept C90509273 @default.
- W2003228681 hasConceptScore W2003228681C111168008 @default.
- W2003228681 hasConceptScore W2003228681C153180895 @default.
- W2003228681 hasConceptScore W2003228681C154945302 @default.
- W2003228681 hasConceptScore W2003228681C19966478 @default.
- W2003228681 hasConceptScore W2003228681C31972630 @default.
- W2003228681 hasConceptScore W2003228681C41008148 @default.
- W2003228681 hasConceptScore W2003228681C57077369 @default.
- W2003228681 hasConceptScore W2003228681C73555534 @default.
- W2003228681 hasConceptScore W2003228681C86369673 @default.
- W2003228681 hasConceptScore W2003228681C90509273 @default.
- W2003228681 hasIssue "12" @default.
- W2003228681 hasLocation W20032286811 @default.
- W2003228681 hasLocation W20032286812 @default.
- W2003228681 hasOpenAccess W2003228681 @default.
- W2003228681 hasPrimaryLocation W20032286811 @default.
- W2003228681 hasRelatedWork W1535005230 @default.
- W2003228681 hasRelatedWork W1937705922 @default.
- W2003228681 hasRelatedWork W2028864324 @default.
- W2003228681 hasRelatedWork W2058063222 @default.
- W2003228681 hasRelatedWork W2074515009 @default.
- W2003228681 hasRelatedWork W2134943711 @default.
- W2003228681 hasRelatedWork W2163622079 @default.
- W2003228681 hasRelatedWork W2734306012 @default.
- W2003228681 hasRelatedWork W2970243024 @default.
- W2003228681 hasRelatedWork W4292862563 @default.
- W2003228681 hasVolume "22" @default.
- W2003228681 isParatext "false" @default.
- W2003228681 isRetracted "false" @default.
- W2003228681 magId "2003228681" @default.
- W2003228681 workType "article" @default.