Shared Control Strategies for BCI-based Quadcopter Control

Abstract

The main objective of this study is to propose a shared control strategy for improving the performance and stability of brain-computer interface (BCI)-based quadcopter movement control. With the advancement of brain imaging devices that are inexpensive, non-invasive, and portable, BCI has recently been implemented in various control applications, for example, wheelchair, telepresence robot, robotic manipulator arm, and quadcopter can be controlled using BCI-based motor imagery task or mental arithmetic task. However, using BCI modalities is still difficult to control a movement of the abovementioned machines with high stability and accuracy. Shared control is a technique that combines inputs and environment information of the system, and then, these inputs will be processed to achieve high efficient output. In this paper, the concept of the shared control will be proposed in three different methods: distance measurement sensor, eye movement detection and Global Positioning System (GPS) for avoiding an obstacle of BCI-based quadcopter control.