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A user wears an EEG cap to detect brain signals and EMG electrodes to detect muscle signals.
Researchers from MIT (Massachusetts Institute of Technology) have created a way to control robots more automatically, using hand gestures and brainwaves.
The team connected the power of brain signals called “error-related potentials” (ErrPs), which naturally occur when people notice a mistake. The system monitors the brain activity of a person observing robotic work, and if an ErrP occurs the robot pauses its activity so that the user can correct it. This occurs via an interface that measures muscle activity; the person makes hand gestures to choose the correct option for the robot. If there is no mistake the robot operates autonomously, and if the mistake is detected using brain signals, the robot asks for help.
The project’s head author, Joseph DelPreto, said that the invention is particularly important because unlike traditional robotic management, users do not need to think in a prescribed way. “The machine adapts to you, and not the other way around,” he said, adding that the system “makes communicating with a robot more like communicating with another person.”
“We’d like to move away from a world where people have to adapt to the constraints of machines,” said project supervisor Daniela Rus. “Approaches like this show that it’s very much possible to develop robotic systems that are a more natural and intuitive extension of us.”
As indicated engadget.com “in one trial, the team used “Baxter”, a robot from Rethink Robotics, to move a power drill to one of three possible targets on the body of a mock plane. With human supervision, Baxter went from choosing the correct target 70 percent of the time to more than 97 percent of the time. Critically, the system works with people it’s never seen before, so organizations could deploy it in real-world settings without needing to train it on new users”.
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