|6 March 2017|
An electroencephalography (EEG) cap measuring brain signals which is used to correct a robot. The system looks for what are called error-related potentials, which are generated when the brain notices a mistake. If it detects these signals, the robot changes its action. The system works in real-time, classifying brain waves in 10-30 milliseconds.
The team plans to refine the system where it can move beyond “simple binary-choice activities” to handle multi-choice and more complex tasks.
“This work brings us closer to developing effective tools for brain-controlled robots and prostheses. Given how difficult it can be to translate human language into a meaningful signal for robots, work in this area could have a truly profound impact on the future of human-robot collaboration,” Wolfram Burgard, a professor of computer science at the University of Freiburg – who was not involved in the research, told MIT News.
“The paper presenting the work was written by BU PhD candidate Andres F. Salazar-Gomez, CSAIL PhD candidate Joseph DelPreto, and CSAIL research scientist Stephanie Gil under the supervision of Rus and BU professor Frank H. Guenther” MIT News said.