Two-dimensional space target searching based on semi-autonomous navigation and motor imagery for multi-rotor aircraft

A brain computer interface (BCI) system was proposed to realize the two-dimensional indoor space target searching for multi-rotor aircraft. This system consists of semi-autonomous navigation and decision subsystems. The semi-autonomous navigation subsystem is employed to provide feasible directions for the decision subsystem and avoid obstacles semi-automatically for multi-rotor aircraft. The decision subsystem utilizes the cross-correlation (CC) and logistic regression (LR) methods to implement motor imagery (MI) electroencephalogram (EEG) feature extraction and classification, respectively. The actual indoor target searching experiment validates the feasibility and effectiveness of this BCI system. Compared to similar methods, the proposed BCI system reduces the burden of the subjects and the control difficulties. The control precision increases by approximately ±10 cm.