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dc.contributor.advisorShamma, Jeff S.
dc.contributor.authorAlghamdi, Anwaar
dc.date.accessioned2020-09-01T07:45:24Z
dc.date.available2020-09-01T07:45:24Z
dc.date.issued2020-09
dc.identifier.citationAlghamdi, A. (2020). A Game-theoretic Implementation of the Aerial Coverage Problem. KAUST Research Repository. https://doi.org/10.25781/KAUST-Y1E2S
dc.identifier.doi10.25781/KAUST-Y1E2S
dc.identifier.urihttp://hdl.handle.net/10754/664912
dc.description.abstractGame theory can work as a coordination mechanism in multi-agent robotic systems by representing each robot as a player in a game. In ideal scenarios, game theory algorithms guarantee convergence to optimal configurations and have been widely studied for many applications. However, most of the studies focus on theoretical analysis and lack the details of complete demonstrations. In this regard, we implemented a real-time multi-robot system in order to investigate how game-theoretic methods perform in non-idealized settings. An aerial coverage problem was modeled as a potential game, where each aerial vehicle is an independent decision-making player. These players take actions under limited communication, and each is equipped with onboard vision capabilities. Three game-theoretic methods have been modified and implemented to solve this problem. All computations are performed using onboard devices, independent of any ground entity. The performance of the system is analyzed and compared with different tests and configurations
dc.language.isoen
dc.subjectGame Theory
dc.subjectmulti-robot coordination
dc.subjectcoverage problem
dc.subjectsensor networks
dc.titleA Game-theoretic Implementation of the Aerial Coverage Problem
dc.typeThesis
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
thesis.degree.grantorKing Abdullah University of Science and Technology
dc.contributor.committeememberLaleg-Kirati, Taous-Meriem
dc.contributor.committeememberElhoseiny, Mohamed H.
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.nameMaster of Science
refterms.dateFOA2020-09-01T07:45:25Z
kaust.request.doiyes


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