A hybrid brain interface for a humanoid robot assistant

Abstract

We present an advanced approach towards a semi-autonomous, robotic personal assistant for handicapped people. We developed a multi-functional hybrid brain-robot interface that provides a communication channel between humans and a state-of-the-art humanoid robot, Honda's Humanoid Research Robot. Using cortical signals, recorded, processed and translated by an EEG-based brain-machine interface (BMI), human-robot interaction functions independently of users' motor control deficits. By exploiting two distinct cortical activity patterns, P300 and event-related desynchronization (ERD), the interface provides different dimensions for robot control. An empirical study demonstrated the functionality of the BMI guided humanoid robot. All participants could successfully control the robot that accomplished a shopping task.