  his paper presents a simple approach for drone navigation to follow a
predetermined path using visual input only without reliance on a Global
Positioning System (GPS). A Convolutional Neural Network (CNN) is used to
output the steering command of the drone in an end-to-end approach. We tested
our approach in two simulated environments in the Unreal Engine using the
AirSim plugin for drone simulation. Results show that the proposed approach,
despite its simplicity, has average cross track distance less than 2.9 meters
in the simulated environment. We also investigate the significance of data
augmentation in path following. Finally, we conclude by suggesting possible
enhancements for extending our approach to more difficult paths in real life,
in the hope that one day visual navigation will become the norm in GPS-denied
zones.
