Coordinated CRLB-based Control for Tracking Multiple First Responders in 3D Environments
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Papaioannou, Savvas | - |
dc.contributor.author | Kim, Sungjin | - |
dc.contributor.author | Laoudias, Christos | - |
dc.contributor.author | Kolios, Panayiotis | - |
dc.contributor.author | Kim, Sunwoo | - |
dc.contributor.author | Theocharides, Theocharis | - |
dc.contributor.author | Panayiotou, Christos | - |
dc.contributor.author | Polycarpou, Marios | - |
dc.date.accessioned | 2021-07-30T05:13:32Z | - |
dc.date.available | 2021-07-30T05:13:32Z | - |
dc.date.created | 2021-05-11 | - |
dc.date.issued | 2020-09 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/3686 | - |
dc.description.abstract | In this paper we study the problem of tracking a team of first responders with a fleet of autonomous mobile flying agents, operating in 3D environments. We assume that the first responders exhibit stochastic dynamics and evolve inside challenging environments with obstacles and occlusions. As a result, the mobile agents probabilistically receive noisy line-of-sight (LoS), as well as non-line-of-sight (NLoS) range measurements from the first responders. In this work, we propose a novel estimation (i.e., estimating the position of multiple first responders over time) and control (i.e., controlling the movement of the agents) framework based on the Cram?r-Rao lower bound (CRLB). More specifically, we analytically derive the CRLB of the measurement likelihood function which we use as a control criterion to select the optimal joint control actions over all agents, thus achieving optimized tracking performance. The effectiveness of the proposed multi-agent multi-target estimation and control framework is demonstrated through an extensive simulation analysis. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Coordinated CRLB-based Control for Tracking Multiple First Responders in 3D Environments | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sunwoo | - |
dc.identifier.doi | 10.1109/ICUAS48674.2020.9213937 | - |
dc.identifier.scopusid | 2-s2.0-85094966066 | - |
dc.identifier.bibliographicCitation | 2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020, pp.1475 - 1484 | - |
dc.relation.isPartOf | 2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020 | - |
dc.citation.title | 2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020 | - |
dc.citation.startPage | 1475 | - |
dc.citation.endPage | 1484 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Autonomous agents | - |
dc.subject.keywordPlus | Multi agent systems | - |
dc.subject.keywordPlus | Stochastic systems | - |
dc.subject.keywordPlus | Unmanned aerial vehicles (UAV) | - |
dc.subject.keywordPlus | Control framework | - |
dc.subject.keywordPlus | Extensive simulations | - |
dc.subject.keywordPlus | First responders | - |
dc.subject.keywordPlus | Likelihood functions | - |
dc.subject.keywordPlus | Nonline of sight | - |
dc.subject.keywordPlus | Range measurements | - |
dc.subject.keywordPlus | Stochastic dynamics | - |
dc.subject.keywordPlus | Tracking performance | - |
dc.subject.keywordPlus | Mobile agents | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/9213937 | - |
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