Title : Researchers use brain waves to correct robot mistakes: Can you feel me now?
Researchers use brain waves to correct robot mistakes: Can you feel me now?
Article Technology, Researchers use brain waves to correct robot mistakes: Can you feel me now?Image: MIT/CSAILBy Lance Ulanoff2017-03-06 16:17:22 UTC Baxter the robot is blushing. It made yet another embarrassing mistake by placing a spray paint can in the wrong bin. A moment later, the big, red bot makes the right choice, placing a bundle of wire in the wire bin. Baxter smiles at the researcher in front of it, a young woman who’s wearing a rather unattractive electroencephalography (EEG) cap. We’re witnessing a visibly symbiotic relationship between metal and flesh. That’s because Baxter, from Rethink Robotics, and the researcher are connected. Every time the hulking, two-armed robot with a face made out of an animated screen makes a mistake, it’s the researcher’s brainwaves that let it know. “We have the EEG cap connected to a laptop that’s processing the signals,” Joseph DelPreto, of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), said in an interview. DelPreto is a part of a small team of researchers who have figured out how to tap into one of our most readable reactions — namely, "you made a mistake" — and turn it into a language even a robot like Baxter can understand. The signals or brain waves that connect Baxter and the EEG-cap-wearing researcher are called error-related-potentials or “ErrP” and occur naturally in the brain when we make a mistake. The intensity of the error correlates to the strength of the signal. Baxter can’t detect those signals by just looking at a researcher, so they must wear the sensitive EEG cap. It detects those signals and a laptop running the team’s proprietary algorithm (capable of classifying brainwaves in under 30 milliseconds), decides If they indicate an error. If so, the program tells the semi-autonomous Baxter, which is randomly inserting errors into a task it already knows how to do (crafty devil) to change its trajectory or revise its behavior. It’s not exactly robot mind-control, but a step toward it. In fact, it is reminiscent of some of the mind-control gadgets we’ve seen over the last half-dozen years. Most take incredible concentration to make anything happen. This is different. It’s true, said study co-author Stephanie Gil, “many of the [existing] brain-related control tasks do require the human to have a lot of concentration or be trained to modulate their thoughts in a specific way to make these brain signals easier to detect and read.” The team — which plans to present the new work at a conference in May — wanted to avoid training and find naturally-occurring brain activity. The idea of using our own response to mistakes seemed straight forward, especially since we can all identify the feeling we have when we realize that something isn't right. This EEG cap knows when you noticed a mistake. Image: MIT/CSAIL “In this case, we don’t want the human to have to learn to think, act or talk in the way the robot can understand. We want the human to do what’s natural and teach [the] robot to interpret that as input signal,” said Gil. While the EEG cap can easily pick up the ErrPs signal, participants must remain engaged and pay close attention to Baxter’s work. Otherwise, they won’t notice any errors made by the robot, meaning that the researchers won't be able to signal that the robot is wrong. So, how far can this “mind-reading” go? “We do see in our body changes when an error happens. That is biology,” said co-author Andres Salazar-Gomez. An error for humans is almost like a glitch and depending on the degree of the glitch — making a mistake on a test versus hurting a friend's feelings — can trigger several biological responses: Your heart races, your stomach turns over, your pupils dilate. 'In future, we might be able to have people who have never worked with robot or worn a EEG cap or ever had their brain waves measured control robots without any training at all.' Salazar-Gomez said that those physical responses are interesting, but the signals take at least a couple of seconds to transmit and the team needs that information in real-time. What the team does see, Gil said, are some ErrPs signals that are stronger than others, depending on the magnitude of the error, though the cap is designed to read some pretty-faint error signals. Salazar-Gomez also cautioned that these results shouldn't be see as any sort of mind-reading. “The signal we’re collecting is more related to increases in attention,” he said. Parsing out a feeling from those signals hard, if not impossible. “Feelings are very abstract,” he added. Abstract or not, the feeling of a mistake is clear to both the researcher and, in this experiment, Baxter the robot. “It’s a very promising first step,” said Gil. “In future, we might be able to have people who have never worked with robot or worn a EEG cap or ever had their brain waves measured control robots without any training at all.” It’s also likely that this research will extend far beyond Baxter. “We created an abstraction for when a mistake could occur. The current experiment uses Baxter, but we could conceivably use it with any other type of robot or smart devices,” said DelPreto. Which means future robots, which include autonomous cars, prosthetic limbs and robot vacuums, could respond to an ever-wider array of signals picked up from, one would hope, much more attractive EEG caps. http://feeds.mashable.com/~r/mashable/tech/~3/oS8A5uXYzLA/
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