We propose an autonomous flight control method for secure navigation of Unmanned Aerial Vehicles (UAVs). We focus on the relation between flight command given to UAV and the response. According to the flight commands sampled in world coordinate system, we acquire the corresponding 3D moving vectors, which represent moving distances and orientations in 3D space, by employing motion capture system. As the input/output relation implemented in UAV is a black box, our approach acquires the sequential input/output relation between flight command and 3D moving vector by using recurrent neural network. Given sequential flight commands, the model predicts the 3D moving vectors that correspond to the command sequence. We demonstrate that our proposed method yields the desirable command sequence for autonomous control.
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