A 3-class Asynchronous BCI Controlling A Simulated Mobile Robot

Abstract

We present our design and online experiments of a 3-class asynchronous BCI controlling a simulated robot in an indoor environment. Two characteristics of our design have efficiently decreased the false positive rate during the NC (No Control) mode. First, three one-vs-rest LDA classifiers are combined to control the switching between NC and IC (In Control) mode. Second, the hierarchical structure of our controller allows the most reliable class (mental task) in a specific subject to play a dominant role in the robot control. A group of simple rules triggered by local sensor signals are designed for safety and obstacle avoidance in the NC mode. In online experiments, subjects successfully controlled the robot to circumnavigate obstacles and reach small targets in separate rooms.