Brain Computer Interface system based on indoor semi-autonomous navigation and motor imagery for Unmanned Aerial Vehicle control

作者：

Highlights：

• BCI system is proposed to control the UAV continuously by motor imagery and semi-autonomous navigation system.

• The semi-autonomous navigation system is used to provide feasible directions and avoid obstacles.

• The improved cross correlation algorithm is used to extract the MI EEG features.

• The logistic regression algorithm is used to classify the MI EEG features.

摘要

•BCI system is proposed to control the UAV continuously by motor imagery and semi-autonomous navigation system.•The semi-autonomous navigation system is used to provide feasible directions and avoid obstacles.•The improved cross correlation algorithm is used to extract the MI EEG features.•The logistic regression algorithm is used to classify the MI EEG features.

论文关键词：Brain Computer Interface,Motor imagery,Unmanned Aerial Vehicle,Cross-correlation,Logistic regression,Semi-autonomous navigation subsystem

论文评审过程：Available online 24 January 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.01.031