Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/94620
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Industrial and Systems Engineering | en_US |
dc.creator | Tseng, KK | en_US |
dc.creator | Li, J | en_US |
dc.creator | Chang, Y | en_US |
dc.creator | Yung, KL | en_US |
dc.creator | Chan, CY | en_US |
dc.creator | Hsu, CY | en_US |
dc.date.accessioned | 2022-08-25T01:54:12Z | - |
dc.date.available | 2022-08-25T01:54:12Z | - |
dc.identifier.issn | 1751-7575 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/94620 | - |
dc.language.iso | en | en_US |
dc.publisher | Taylor & Francis | en_US |
dc.rights | © 2021 Informa UK Limited, trading as Taylor & Francis Group | en_US |
dc.rights | This is an Accepted Manuscript of an article published by Taylor & Francis in Enterprise Information Systems on 08 Dec 2019 (published online), available at: http://www.tandfonline.com/10.1080/17517575.2019.1698772. | en_US |
dc.subject | Extended kalman filter | en_US |
dc.subject | Motion estimation | en_US |
dc.subject | ORB | en_US |
dc.subject | Planetary rover | en_US |
dc.subject | Simultaneous localisation and mapping | en_US |
dc.subject | System design | en_US |
dc.title | A new architecture for simultaneous localization and mapping : an application of a planetary rover | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 1162 | en_US |
dc.identifier.epage | 1178 | en_US |
dc.identifier.volume | 15 | en_US |
dc.identifier.issue | 8 | en_US |
dc.identifier.doi | 10.1080/17517575.2019.1698772 | en_US |
dcterms.abstract | A new architecture implements one Monocular Simultaneous Localization and Mapping (SLAM) system to track the unconstraint motion of a mobile robot. The modified ORB (Oriented FAST and Rotated BRIEF) features represent the landmarks for designing a grid feature detection algorithm. An upgraded feature matching method has improved the robustness of feature matching. The Modified coVariance Extended Kalman Filter (MVEKF) estimates the multiple dimension states of the free moving visual sensor instead of the familiar Extended Kalman Filter (EKF). The simulation navigation of Lunar and Mars surfaces proves that the proposed method is robust and efficient. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Enterprise information systems, 2021, v. 15, no. 8, p. 1162-1178 | en_US |
dcterms.isPartOf | Enterprise information systems | en_US |
dcterms.issued | 2021 | - |
dc.identifier.scopus | 2-s2.0-85076435827 | - |
dc.identifier.eissn | 1751-7583 | en_US |
dc.description.validate | 202208 bcww | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | ISE-0192 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Shenzhen Government; Shenzhen Development and Reform Commission through Shenzhen Development and Reform; The Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 60269411 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Yung_New_Architecture_Simultaneous.pdf | Pre-Published version | 2.22 MB | Adobe PDF | View/Open |
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