Table tennis robot defeats some of world’s best players – why this has major implications for robotics |
A table tennis robot has outperformed elite players in recent evaluations. The robot, called Ace, marks a significant step toward artificial intelligence (AI) systems that can operate in fast, uncertain, real-world environments.
In the tests, the autonomous robot won three out of five matches against elite players – competitive athletes with over ten years’ experience and an average of 20 hours weekly training. The robot, developed by Sony AI, lost both matches against players in professional Japanese leagues, but did win a game against one of them. The system is described in detail in a recent paper published in Nature.
AI has spent decades mastering games. It has repeatedly outperformed the best humans in everything from complex video games like StarCraft II to chess – where modern programs now far exceed human ratings.
Landmark systems such as Deep Blue and AlphaGo have confirmed that, given clear rules and enough data, AI can achieve superhuman performance. But these victories all shared one key feature: they happened in controlled, digital environments.
At first glance, table tennis might seem like an unusual benchmark for artificial intelligence. In reality, it is one of the most demanding imaginable. The ball can travel faster than 20 metres per second, giving players less than half a second to react.
On top of that, spin introduces enormous complexity. A ball rotating at extreme speeds can curve mid-air and rebound unpredictably off the table. For humans, interpreting spin is largely intuitive. For robots, it has been a longstanding obstacle.
Earlier table tennis robotic systems such as Forpheus, developed by Japanese company Omron, addressed this by simplifying the game – using controlled ball........