Online deep learning for improved trajectory tracking of unmanned aerial vehicles using expert knowledge

This work presents an online learning-based control method for improved trajectory tracking of unmanned aerial vehicles using both deep learning and expert knowledge. The proposed method does not require the exact model of the system to be controlled, and it is robust against variations in system dy...

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Bibliographic Details
Main Authors: Sarabakha, Andriy, Kayacan, Erdal
Other Authors: School of Mechanical and Aerospace Engineering
Format: Conference Paper
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10356/141407