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Found 5 papers, 1 papers with code
Uncertainty-Aware Guidance for Target Tracking subject to Intermittent Measurements using Motion Model Learning
This neural network (NN)-based motion model serves as the prediction step in a particle filter for target state estimation and uncertainty quantification.
Deep Nonlinear Adaptive Control for Unmanned Aerial Systems Operating under Dynamic Uncertainties
Recent literature in the field of machine learning (ML) control has shown promising theoretical results for a Deep Neural Network (DNN) based Nonlinear Adaptive Controller (DNAC) capable of achieving trajectory tracking for nonlinear systems.
Information-Aware Guidance for Magnetic Anomaly based Navigation
In the absence of an absolute positioning system, such as GPS, autonomous vehicles are subject to accumulation of positional error which can interfere with reliable performance.
Going Beyond RF: How AI-enabled Multimodal Beamforming will Shape the NextG Standard
Incorporating artificial intelligence and machine learning (AI/ML) methods within the 5G wireless standard promises autonomous network behavior and ultra-low-latency reconfiguration.
A summary on the UD Kalman Filter
This document contains a concise and unified reference for one of the existing mechanizations of the UD Kalman filter.
