Planování trajektorie pro skupinu helikoptér v neznamém prostředí s omezením na množství sdílených informací
Multi-UAV trajectory planning in unknown environments with limited information sharing
Type of document
diplomová prácemaster thesis
Author
Afzal Ahmad
Supervisor
Spurný Vojtěch
Opponent
Petříček Tomáš
Field of study
Umělá inteligenceStudy program
Open InformaticsInstitutions assigning rank
katedra počítačůRights
A 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.htmlVysokoškolská 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.html
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A 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. A 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.
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