Getting robots to do what we want often requires giving them explicit commands for very specific tasks. But new research suggests that we could one day control them in much more intuitive ways.
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Boston University has developed a feedback system that lets people use their thoughts to correct robots instantly when the machines make mistakes. Using data from an electroencephalography (EEG) monitor that records brain activity, the system can detect—in the space of 10 to 30 milliseconds—if a person notices an error as a robot performs an object-sorting task.
“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, a senior author on a paper about the research being presented at the IEEE International Conference on Robotics and Automation in May. “A streamlined approach like that would improve our abilities to supervise factory robots, driverless cars, and other technologies we haven’t even invented yet.”
Past work in robotics controlled by EEG has required training humans to think in a prescribed way that computers can recognize. For example, an operator might have to look at one of two bright light displays, each of which corresponds to a different task for the robot to execute. But the training process and the act of modulating one’s thoughts can be taxing, particularly for people who supervise tasks in navigation or construction that require intense concentration.
Rus’s team wanted to make the experience more natural. To do that, they focused on brain signals called error-related potentials (ErrPs), which are generated whenever our brains notice a mistake. As the robot—in this case, a humanoid robot named Baxter from Rethink Robotics, the company led by former CSAIL director Rodney Brooks—indicates which choice it plans to make in a binary activity, the system uses ErrPs to determine whether the human agrees with the decision.
“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.”
Renewables are set to soar
The world will likely witness a wind and solar boom over the next five years, as costs decline and nations raise their climate ambitions.
How Facebook and Google fund global misinformation
The tech giants are paying millions of dollars to the operators of clickbait pages, bankrolling the deterioration of information ecosystems around the world.
This scientist now believes covid started in Wuhan’s wet market. Here’s why.
How a veteran virologist found fresh evidence to back up the theory that covid jumped from animals to humans in a notorious Chinese market—rather than emerged from a lab leak.
We won’t know how bad omicron is for another month
Gene sequencing gave an early alert about the latest covid variant. But we'll only know if omicron is a problem by watching it spread.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.