Quadcopter Control in Three-Dimensional Space Using SSVEP and Motor Imagery-Based Brain-Computer Interface

Abstract

The use of quadcopters is increasing in more and more fields in daily lives and is not limited to military applications from where they originated. They are moving towards entertainment, real-estate, delivery, and so on. The unconventional man-machine interface is a generous topic to explore now and in the future. One among them is Brain-Computer Interface (BCI) which has proven to be a very powerful tool to establish communication without any motor movements of the limbs. BCI based on motor imagery (MI) requires very long training sessions to be used effectively. On the other hand, BCI based on steady-state visual evoked potential (SSVEP) has a limited number of sessions because electroencephalography (EEG) signal detection time (signal window length) and accuracy get the highest priority as performance parameters. This paper presents mathematical modeling and numerical simulation of a quadcopter and BCI. An application is presented with the help of a DJI Flight Simulator and an Emotiv Epoc+ headset.