The Unexpected Humanity of Robot Soccer
When Google’s AlphaGo computer program triumphed over a Go expert earlier this year, a human member of the Google team had to physically move the pieces. Manuela Veloso, the head of Carnegie Mellon’s machine learning department, would have done it differently. “I’d require the machine to move the pieces like I do,” she says. “That’s the world in which I live, which is a physical world.”
It sounds simple enough. If Google can make cars that drive themselves, surely it could add robotic arms to a Go match. Even in 1997, I.B.M. could have given Deep Blue robotic arms in its match against Garry Kasparov. To Veloso, though, the challenge is not in building a robot to play on a given board in given conditions, but rather to build one able to play on any board. “Imagine all the different types of chess pieces that humans handle perfectly fine. How would we get a robot to detect these pieces and move them on any type of board, with any number of lighting conditions, and never let the piece fall except on the right square? Oh God,” she says.
And if the idiosyncrasies of static chess pieces are hard for modern robotics, imagine how hard it would be to deal with a chaotic, rolling soccer ball. Then add a whole team of other robots chasing that same ball. That’s
