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  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