A Social-GAN-style LSTM generator predicts UAS landing trajectories and beats a Gaussian Mixture Regression baseline on real drone data, though the advantage disappears on simulated data beyond four steps.
A recurrent neural network approach for aircraft trajectory prediction with weather features from sherlock,
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Landing Trajectory Prediction for UAS Based on Generative Adversarial Network
A Social-GAN-style LSTM generator predicts UAS landing trajectories and beats a Gaussian Mixture Regression baseline on real drone data, though the advantage disappears on simulated data beyond four steps.