Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/6455
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical Engineering | - |
dc.creator | Huang, GQ | - |
dc.creator | Rad, AB | - |
dc.creator | Wong, YK | - |
dc.date.accessioned | 2014-12-11T08:25:53Z | - |
dc.date.available | 2014-12-11T08:25:53Z | - |
dc.identifier.issn | 1729-8806 | - |
dc.identifier.uri | http://hdl.handle.net/10397/6455 | - |
dc.language.iso | en | en_US |
dc.publisher | InTech | en_US |
dc.rights | This work is licensed under the terms of the Creative Commons Attribution 3.0 Unported License (http://creativecommons.org/licenses/by/3.0/) | en_US |
dc.subject | Mapping | en_US |
dc.subject | Tracking | en_US |
dc.subject | Mobile robots | en_US |
dc.title | A new solution to map dynamic indoor environments | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.description.otherinformation | Author name used in this publication: G. Q. Huang | en_US |
dc.description.otherinformation | Author name used in this publication: Y. K. Wong | en_US |
dc.identifier.spage | 199 | - |
dc.identifier.epage | 210 | - |
dc.identifier.volume | 3 | - |
dc.identifier.issue | 2 | - |
dc.identifier.doi | 10.5772/5737 | - |
dcterms.abstract | In this paper, we propose a new algorithm of mapping dynamic indoor environments. Instead of accurate but expensive laser, we employ sonar and camera to map dynamic structured indoor environments. Based on fuzzy-tuned grid-based map (FTGBM), we use two methods: sonar temporal difference (STD) and statistical background subtraction (SBS), to detect and track moving objects when mapping dynamic environments. The former is a consistency-based method realized by monitoring a sequence of temporal lattice maps for a certain number of measurement periods to detect moving objects by using sonars; and the latter is a background subtraction technique which adopts an expectation maximization (EM) learned 3-class mixture of Gaussians to model the nonstationary background relied on sufficient update during mapping process. After finding the moving objects, we propose a fuzzy-tuned integration (FTI) method to incorporate the results of motion detection into the mapping process. The simulation and experiment demonstrate the capabilities of our approach. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | International journal of advanced robotic systems, 2006, v. 3, no. 2, p. 199-210 | - |
dcterms.isPartOf | International journal of advanced robotic systems | - |
dcterms.issued | 2006 | - |
dc.identifier.scopus | 2-s2.0-33750176788 | - |
dc.identifier.eissn | 1729-8814 | - |
dc.identifier.rosgroupid | r32286 | - |
dc.description.ros | 2006-2007 > Academic research: refereed > Publication in refereed journal | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Huang_Map_Dynamic_Indoor.pdf | 819.32 kB | Adobe PDF | View/Open |
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