A Drone Flight Control Using Brain Computer Interface and Artificial Intelligence
Mokhles M. Abdulghani, Arthur A. Harden, Khalid H. Abed
Abstract
The human mind is a truly remarkable thing that does so much that we are not even aware of. Controlling machines using the concept of Brain-Computer Interface (BCI) is a practical method that opens the way to a fully synchronized method between human thoughts and controlled objects. Using BCI to control a drone will open the way toward smooth and high-response flight. Deep learning is a new-age skill that has made many breakthroughs and influenced modern technologies. It has made it possible to predict and identify even the most complex and abstract patterns that even we humans would be very challenged to catch ourselves. In this paper, a method of controlling a drone using BCI has been presented using an 8-channel Electroencephalogram (EEG) headset. Deep learning has been employed to process and classify human brain waves. After testing the resulting deep learning algorithm, the overall classification accuracy was 90% to distinguish between four different movements of the drone.