| KEYWORD |
Physics-guided neural networks for the robust control of drones
keywords DRONES, MACHINE LEARNING, ROBOTICS, UAV
Reference persons ALESSANDRO RIZZO
Thesis type EXPERIMENTAL AND SIMULATION
Description The thesis aims at developing robust control algorithms for unmanned aerial vehicles, based on or complemented by machine learning techniques. In particular, we aim at using Physics-guided neural networks, toward gaining more interpretability of the control action and, possibly, some guarantee on the control performance. A review of the main concepts surrounding this thesis is attached.
See also 2020_jirs_gu_annsurvey.pdf
Deadline 21/09/2021
PROPONI LA TUA CANDIDATURA