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Multi-UAV trajectory planning in unknown environments with limited information sharing



dc.contributor.advisorSpurný Vojtěch
dc.contributor.authorAfzal Ahmad
dc.date.accessioned2022-06-08T22:54:12Z
dc.date.available2022-06-08T22:54:12Z
dc.date.issued2022-06-08
dc.identifierKOS-1198417418505
dc.identifier.urihttp://hdl.handle.net/10467/101454
dc.description.abstractA system composed of multiple UAVs can solve several complex tasks which are either difficult or unfeasible with a single UAV. Safe and fast operation are crucial when multiple UAVs are simultaneously working in a shared environment. This thesis focuses on studying and developing a method for collision-free trajectory planning by a multi-UAV system. The proposed method uses sensors on-board the UAV to create an online map of the environment and detect the motion of other UAVs. Theses detections are employed to predict the future trajectory of the UAVs. The map along with the predicted trajectories is used to design a collision-free trajectory to a pre-specified goal. The proposed method is decentralized and does not require any prior information about the environment or other UAVs which makes it easier to scale to large multi-UAV systems. The method is also independent of any external localization infrastructure making it ideal for real-world applications.cze
dc.description.abstractA system composed of multiple UAVs can solve several complex tasks which are either difficult or unfeasible with a single UAV. Safe and fast operation are crucial when multiple UAVs are simultaneously working in a shared environment. This thesis focuses on studying and developing a method for collision-free trajectory planning by a multi-UAV system. The proposed method uses sensors on-board the UAV to create an online map of the environment and detect the motion of other UAVs. Theses detections are employed to predict the future trajectory of the UAVs. The map along with the predicted trajectories is used to design a collision-free trajectory to a pre-specified goal. The proposed method is decentralized and does not require any prior information about the environment or other UAVs which makes it easier to scale to large multi-UAV systems. The method is also independent of any external localization infrastructure making it ideal for real-world applications.eng
dc.publisherČeské vysoké učení technické v Praze. Vypočetní a informační centrum.cze
dc.publisherCzech Technical University in Prague. Computing and Information Centre.eng
dc.rightsA university thesis is a work protected by the Copyright Act. Extracts, copies and transcripts of the thesis are allowed for personal use only and at one?s own expense. The use of thesis should be in compliance with the Copyright Act http://www.mkcr.cz/assets/autorske-pravo/01-3982006.pdf and the citation ethics http://knihovny.cvut.cz/vychova/vskp.htmleng
dc.rightsVysokoškolská závěrečná práce je dílo chráněné autorským zákonem. Je možné pořizovat z něj na své náklady a pro svoji osobní potřebu výpisy, opisy a rozmnoženiny. Jeho využití musí být v souladu s autorským zákonem http://www.mkcr.cz/assets/autorske-pravo/01-3982006.pdf a citační etikou http://knihovny.cvut.cz/vychova/vskp.htmlcze
dc.subjectUnmanned Aerial Vehiclescze
dc.subjectMulti-UAV Path Planningcze
dc.subjectCollision Avoidancecze
dc.subjectDecentralized Systemscze
dc.subjectMotion Predictioncze
dc.subjectUnmanned Aerial Vehicleseng
dc.subjectMulti-UAV Path Planningeng
dc.subjectCollision Avoidanceeng
dc.subjectDecentralized Systemseng
dc.subjectMotion Predictioneng
dc.titlePlanování trajektorie pro skupinu helikoptér v neznamém prostředí s omezením na množství sdílených informacícze
dc.titleMulti-UAV trajectory planning in unknown environments with limited information sharingeng
dc.typediplomová prácecze
dc.typemaster thesiseng
dc.contributor.refereePetříček Tomáš
theses.degree.disciplineUmělá inteligencecze
theses.degree.grantorkatedra počítačůcze
theses.degree.programmeOpen Informaticscze


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