Rock-paper-scissors should be a simple game. But it requires strategy, psychology, instinct. Does your opponent always pick rock, like Michael Bluth in Arrested Development or Bart in The Simpsons? If you put up paper and are met with scissors, do you pick the sheers yourself in the subsequent round, or stick with paper on the assumption that your rival will next pick rock.
If you assign your rock-paper-scissors to this robot surrogate, though, you’ll never fail. That’s because the machine’s high-speed vision analyzes the way its opponent is shaping his or her hand and is able to identify within one millisecond the weapon that is about to be thrown its way. Once it can tell whether it will face rock, scissors, or paper, the robot can figure out what it should do to win. “[I]t all happens so fast that it’s more or less impossible to tell that the robot is waiting until you commit yourself before it makes its move,” says Evan Ackerman on IEEE Spectrum’s Automaton blog. The result: The bot wins 100 percent of the time.
Researchers at the University of Tokyo’s Ishikawa Oku Laboratory call this a “human-machine cooperation system.” Though it doesn’t feel like the robot is “cooperating” when it wins by taking advantage of our slower reflexes, its creators say the technology could make it easier for man and bot to work together—say, along a factory production line.
This isn’t the first such bot, though it may be the most competitive. Rock, paper, scissors projects are pretty popular with robotics hobbyists. In the video below from 2008, in which a child shows off the machine he builts.
The robot BERTI, or Bristol Elumotion Robotic Torso 1, showed off its RPS game when it debuted at London’s Science Museum in 2009. Like the Japanese machine’s promise in “human-machine cooperation,” BERTI’s creators spoke of its potential to help people who are afflicted with Parkinson’s disease or have suffered a stroke.
No word yet on what happens when two rock-paper-scissor robots face off against each other.