UAV control in 2D space based on brain computer interface

An Electroencephalogram (EEG)-based Brain Computer Interface (BCI) system is put forward to implement the continuous control of an Unmanned Aerial Vehicle (UAV) in the indoor 2D space using the motor imagery (MI) tasks. This BCI system utilizes the discriminative time- and frequency-dependent spatial filter to extract the EEG features of MI tasks. The adaptive linear discriminant analysis (LDA) method is utilized to accomplish the classification of these extracted features. The calibration experiment and actual indoor 2D space controlling experiment presented the effectiveness and feasibility of using this BCI system to achieve the indoor 2D space continuous control of UAV.