Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCA.2013.6564992
DC FieldValue
dc.titleMission planning of autonomous UAVs for urban surveillance with evolutionary algorithms
dc.contributor.authorGeng, L.
dc.contributor.authorZhang, Y.F.
dc.contributor.authorWang, J.J.
dc.contributor.authorFuh, J.Y.H.
dc.contributor.authorTeo, S.H.
dc.date.accessioned2014-06-19T05:37:17Z
dc.date.available2014-06-19T05:37:17Z
dc.date.issued2013
dc.identifier.citationGeng, L.,Zhang, Y.F.,Wang, J.J.,Fuh, J.Y.H.,Teo, S.H. (2013). Mission planning of autonomous UAVs for urban surveillance with evolutionary algorithms. IEEE International Conference on Control and Automation, ICCA : 828-833. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICCA.2013.6564992" target="_blank">https://doi.org/10.1109/ICCA.2013.6564992</a>
dc.identifier.isbn9781467347075
dc.identifier.issn19483449
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/73617
dc.description.abstractIn this paper, a mission planning system is presented that generates mission plans for a group of unmanned aerial vehicles (UAVs) to provide continuous surveillance over an urban area. Given the information of terrain and buildings in the target area, a two-stage approach is employed to solve the problem. In the first stage, a set of camera locations called the vantage set is generated that provides complete coverage of the target area. In the second stage, one or several UAVs are determined to collectively share the vantage set and their individual paths are generated to carry out the continuous surveillance duty. In both stages, evolutionary algorithms (genetic algorithm for vantage set generation and ant colony system for UAV/path planning) are used to search for the optimal solution. During the search, constraints such as the flying capabilities of UAVs and collision avoidance are imposed to guarantee the feasibility of the final result. © 2013 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICCA.2013.6564992
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1109/ICCA.2013.6564992
dc.description.sourcetitleIEEE International Conference on Control and Automation, ICCA
dc.description.page828-833
dc.identifier.isiutNOT_IN_WOS
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