Brain-Controlled Robots Becoming a Reality at MIT

The human needs to wear an EEG cap that measures their brain signals. The system looks for brain signals called "error-related potentials" that are generated when the brain notices a mistake has been made.


Robots aren’t supposed to make mistakes. But if they do, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Boston University have developed a way to correct the robot’s actions by using a person’s electroencephalography (EEG) brain signals.

The human needs to wear an EEG cap that measures their brain signals. The system looks for brain signals called “error-related potentials” (ErrPs) that are generated when the brain notices a mistake has been made. As the robot indicates which choice it plans to make, the system uses ErrPs to determine if the human agrees with the decision.

The system works in real-time, classifying brain waves in 10-30 milliseconds. The system, which is being tested on Rethink Robotics’ Baxter, even make the robot feel embarrassed when it makes a mistake. The idea is to make robots a more natural extension of humans.

Paper: Correcting Robot Mistakes in Real Time Using EEG Signals

“Imagine being able to instantaneously tell a robot to do a certain action, without needing to type a command, push a button or even say a word,” says CSAIL director Daniela Rus, who won the 2017 Engelberger Robotics Awards for Education. “A streamlined approach like that would improve our abilities to supervise factory robots, driverless cars and other technologies we haven’t even invented yet.”

The team’s next step is to refine the system so that it can handle multiple-choice and other complex tasks besides simple binary-choice activities, which is what you see in the video atop this page.

“As you watch the robot, all you have to do is mentally agree or disagree with what it is doing,” says Rus. “You don’t have to train yourself to think in a certain way -  the machine adapts to you, and not the other way around.”

In addition to monitoring ErrPs, the team also detects “secondary errors” that occur when the system doesn’t notice the human’s original correction. “If the robot’s not sure about its decision, it can trigger a human response to get a more accurate answer,” the team says. “These signals can dramatically improve accuracy, creating a continuous dialogue between human and robot in communicating their choices.”

“This work brings us closer to developing effective tools for brain-controlled robots and prostheses,” says Wolfram Burgard, a professor of computer science at the University of Freiburg who was not involved in the research. “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.”




About the Author

Steve Crowe · Steve Crowe is managing editor of Robotics Trends. Steve has been writing about technology since 2008. He lives in Belchertown, MA with his wife and daughter.
Contact Steve Crowe: scrowe@ehpub.com  ·  View More by Steve Crowe.




Comments



Log in to leave a Comment

Article Topics

Future Tech · Science & Technology · News · Media · Videos · MIT · All Topics


Editors’ Picks

Autonomous Snake-like Robot to Support Search-and-Rescue
Worcester Polytechnic Institute is creating autonomous snake-like robots that can navigate through...

Love Writing About Robotics and AI? Robotics Trends is Hiring!
Robotics Trends and sister site Robotics Business Review are growing and adding...

WiBotic PowerPad Wirelessly Charges Drones
WiBotic’s PowerPad wirelessly charges everything from large industrial drones to smaller...

Meet Jing Xiao: WPI’s New Director of Robotics
In January 2018, Jing Xiao will become the new director of the Robotics...