The Use of Deep Reinforcement Learning for Flying a Drone (CROSBI ID 297982)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Domitran, Sandro ; Bagić Babac, Marina
engleski
The Use of Deep Reinforcement Learning for Flying a Drone
Nowadays, unmanned aerial vehicles, commonly known as drones, are used for many different purposes. However, it is still a challenging task to fly a drone, which limits its potential for doing more useful things. This paper shows how to design, develop and test an ML-Agent simulation environment by using the Unity engine and the deep reinforcement learning algorithm. First, the drone model needs to be imported in a simulating environment where it should have an ability to fly, and then it should be made to fly using deep reinforcement learning. In addition, the drone can learn to perform a certain task to elaborate the benefits of this approach.
unmanned aerial vehicle ; flight control ; VTOL Tailsitter UAV ; machine learning ; deep reinforcement learning
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Podaci o izdanju
37 (5)
2021.
1165-1176
objavljeno
1016-2364
10.6688/JISE.202109_37(5).0012