Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76746
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dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorYuan, WM-
dc.creatorGanganath, N-
dc.creatorCheng, CT-
dc.creatorQing, G-
dc.creatorLau, FCM-
dc.date.accessioned2018-06-05T07:28:52Z-
dc.date.available2018-06-05T07:28:52Z-
dc.identifier.isbn978-1-5386-4881-0 (electronic)en_US
dc.identifier.isbn978-1-5386-4882-7 (print on demand(PoD))en_US
dc.identifier.urihttp://hdl.handle.net/10397/76746-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Yuan, W., Ganganath, N., Cheng, C. T., Qing, G., & Lau, F. C. M. (2018). Path Planning for Semi-Flocking-Controlled Mobile Sensor Networks on Mobility Maps. In IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE is available at https://dx.doi.org/10.1109/ISCAS.2018.8351449en_US
dc.subjectSemi-flockingen_US
dc.subjectPath planningen_US
dc.subjectMobility mapsen_US
dc.subjectTarget trackingen_US
dc.subjectMobile sensor networksen_US
dc.titlePath planning for semi-flocking-controlled mobile sensor networks on mobility mapsen_US
dc.typeConference Paperen_US
dc.identifier.spage1en_US
dc.identifier.epage5en_US
dc.identifier.doi10.1109/ISCAS.2018.8351449en_US
dcterms.abstractMobile sensor networks (MSNs) are useful in monitoring outdoor environments. Semi-flocking algorithms have been proven to be efficient in controlling MSNs in area sensing and target tracking applications. Even though outdoor environments may consist of irregular regions with different traverse costs, existing semi-flocking algorithms assume an area of interest (AoI) to be regular and with uniform costs. Such an assumption limits target tracking capabilities of a MSN. In this work, we model operating terrains using a mobility map that incorporates the speed limits of different sub-regions. To gather the required number of mobile sensor nodes for target tracking, an A∗ heuristic search algorithm is used to find time-efficient paths connecting nodes to targets. Nodes can acquire navigation information using the A∗-based path planning module and then traverse along the time-efficient paths until they reach the targets. Simulation results verify the effectiveness of the proposed method over an existing semi-flocking algorithm.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation2018 International Symposium on Circuits and Systems (ISCAS), Florence, Italy, 27-30 May 2018, p. 1-5-
dcterms.issued2018-
dc.relation.conferenceIEEE International Symposium on Circuits and Systems [ISCAS]en_US
dc.identifier.eissn2379-447Xen_US
dc.identifier.rosgroupid2017004537-
dc.description.ros2017-2018 > Academic research: refereed > Refereed conference paper-
dc.description.validate201806 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0189-n02en_US
dc.description.pubStatusPublisheden_US
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