Human-Robot Interaction Using Brain-Computer Interface Based on EEG Signal Decoding

This study describes a new approach to a problem of the human-robot interaction for remote control of robot behavior. Finding a solution to this problem is important for providing control of robots and unmanned vehicles. At the interaction a human operator can form commands for robot control. It is proposed to use a noninvasive brain-computer interface based on the decoding of signals of brain activity during motor imagery to generate the supervisor commands for robot control. The principles of the interaction of human as an operator and robot as an executor are considered. Using the brain-computer interface the operator can change robot behavior without any special movements and modules embedded into robot’s program. The study aimed to development of the human-robot interaction system for non-direct control of the robot behavior based on the brain-computer interface for classification of EEG patterns of imaginary movements of one hand fingers in real-time. Example of such human-robot interaction realization for Nao robot with neurofeedback is considered.