Trajectory prediction of UAV Based on LSTM

In the autonomous UAV cruise mission, safety and reliability are critical and challenging issues. From the historical UAV accidents, it is clear that ensuring UAV operation safety is important. In order to ensure that UAV can cruise according to the preset safe path, a prediction model based on deep neural network is proposed in this paper. The stacked Bidirectional and Unidirectional LSTM (SBULSTM) network uses the four positions before the current time of UAV to predict the position of the next time during cruise operation. UAV is safely controlled according to the linear distance between the real position and the predicted position. When the linear distance is not greater than the set threshold, UAV can independently and safely complete the cruise task.