| Popis: |
The article considers one of the aspects of the situational awareness problem for control systems of unmanned vehicles. We interpret this problem as getting information about the current situation in which, for example, an unmanned aerial vehicle (UAV) is operating. This information is required as source data for decision-making in the UAV behavior control process. One possible component of situational awareness is information about objects in the space surrounding the UAV. At the same time, it is important to know along which trajectories these objects move. Also, we need to predict the motion of the observed objects. We consider this task in the article as a formation example for one of the elements of situational awareness. To solve this problem, we prepare a data set using the FlightGear flight simulator. We extract from this set the training, validation, and test sets required to obtain a neural network that predicts the trajectory of the object being tracked. Then, based on the collected data that characterize the behavior of the desired object, we design a neural network model based on recurrent neural networks to solve the problem of predicting the trajectory of a dynamic object. |
