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dc.contributor.authorVan Nguyen, H.
dc.contributor.authorVo, B.N.
dc.contributor.authorVo, Ba Tuong
dc.contributor.authorRezatofighi, H.
dc.contributor.authorRanasinghe, D.C.
dc.date.accessioned2024-12-03T08:15:00Z
dc.date.available2024-12-03T08:15:00Z
dc.date.issued2024
dc.identifier.citationVan Nguyen, H. and Vo, B.N. and Vo, B.T. and Rezatofighi, H. and Ranasinghe, D.C. 2024. Multi-Objective Multi-Agent Planning for Discovering and Tracking Multiple Mobile Objects. IEEE Transactions on Signal Processing. 72: pp. 3669-3685.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/96498
dc.identifier.doi10.1109/TSP.2024.3423755
dc.description.abstract

—We consider the online planning problem for a team of agents to discover and track an unknown and time-varying number of moving objects from onboard sensor measurements with uncertain measurement-object origins. Since the onboard sensors have limited field-of-views, the usual planning strategy based solely on either tracking detected objects or discovering unseen objects is inadequate. To address this, we formulate a new information-based multi-objective multi-agent control problem, cast as a partially observable Markov decision process (POMDP). The resulting multi-agent planning problem is exponentially complex due to the unknown data association between objects and multi-sensor measurements; hence, computing an optimal control action is intractable. We prove that the proposed multi-objective value function is a monotone submodular set function, which admits low-cost suboptimal solutions via greedy search with a tight optimality bound. The resulting planning algorithm has a linear complexity in the number of objects and measurements across the sensors, and quadratic in the number of agents. We demonstrate the proposed solution via a series of numerical experiments with a real-world dataset.

dc.titleMulti-Objective Multi-Agent Planning for Discovering and Tracking Multiple Mobile Objects
dc.typeJournal Article
dcterms.source.volume72
dcterms.source.startPage3669
dcterms.source.endPage3685
dcterms.source.issn1053-587X
dcterms.source.titleIEEE Transactions on Signal Processing
dc.date.updated2024-12-03T08:14:59Z
curtin.departmentSchool of Elec Eng, Comp and Math Sci (EECMS)
curtin.accessStatusIn process
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidVo, Ba Tuong [0000-0002-3954-238X]
curtin.contributor.orcidNguyen, Hoa [0000-0002-6878-5102]
dcterms.source.eissn1941-0476
curtin.contributor.scopusauthoridVo, Ba Tuong [9846846600]
curtin.contributor.scopusauthoridNguyen, Hoa [57205442806]
curtin.repositoryagreementV3


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