engleski

A Machine Learning Approach to Flight Control of a VTOL Tailsitter UAV

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. The goal of this paper is to explain how to fly a drone using a machine learning approach, which should make its flight more accurate, efficient and stable. In this paper, we propose an artificial-intelligence-based flight control of unmanned aerial vehicles in a realistic simulated environment. In addition, the drone can learn to perform a certain task to elaborate the benefits of this approach.

unmanned aerial vehicle ; UAV flight control ; machine learning ; reinforcement learning

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