Brain-Machine Interfaces for Robotic Control

In a collaboration between the Guenther lab and the Neuromorphics lab at Boston University, we developed an EEG-based brain-machine interface (BMI) for controlling an adaptive mobile agent consisting of an iRobot Create enhanced with a rotatable camera and robotic arm. Using EEG signals, the user can navigate the mobile robot to a desired location in a room, orient the camera to fixate on a target object, and pick up an attended object with the robotic arm. The video below, created by Sean Lorenz, illustrates the navigation component of this system.

In a second collaboration with Dr. Daniela Rus and colleagues at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), we are developing a BMI that uses error-related potentials detected in a human observer using electroencephalography (EEG) to correct movements of a robotic arm. The video below, created by CSAIL, illustrates this system, which has received widespread coverage in the popular press.