Google DeepMind Develops Human-Level Competitive Ping-Pong Robot

Google’s AI research laboratory, Google Deepmind, developed a new human-level competitive ping-pong robot. The company published a paper with the technical details and videos of the AI-powered table tennis bot and announced it on social media.

“Meet our AI-powered robot that’s ready to play table tennis,” shared the company on X, “It’s the first agent to achieve amateur human-level performance in this sport.”

Meet our AI-powered robot that’s ready to play table tennis. 🤖🏓

It’s the first agent to achieve amateur human level performance in this sport. Here’s how it works. 🧵 pic.twitter.com/AxwbRQwYiB

— Google DeepMind (@GoogleDeepMind) August 8, 2024

In the paper, “Achieving Human Level Competitive Robot Table Tennis,” researchers explain that achieving human performance—including speed, accuracy, adaptability, and decision-making— is one of the main goals in the robotics research community and they have achieved this with the “the first learned robot agent that reaches amateur human-level performance in competitive table tennis.”

In the thread on X, Google Deepmind explains that the robotic tennis table has been a benchmark for researchers since 1980.

Google DeepMind trained the robot with a dataset of initial information and the intelligence practiced to learn different skills from the library handed. It rehearsed first in a simulated environment until it was ready to practice against real humans.

Researchers made the ping pong robot compete against 29 human players—with different levels, from beginner to advanced— concluding that it had intermediate amateur skills.

“The robot won 45% of matches and 46% of games,” shared the research team in the document. “Broken down by skill level, we see the robot won all matches against beginners, lost all matches against the advanced and advanced+ players, and won 55% of matches against intermediate players. This strongly suggests our agent achieved intermediate-level human play on rallies.”

Google DeepMind also explained that the robot is capable of collecting data on its performance after playing against humans to improve its skills during simulation mode.

“Going in our aim was to have the robot be at an intermediate level. Amazingly it did just that, all the hard work paid off,” said Barney J. Reed, a Professional Table Tennis Coach who participated in the research. “I feel the robot exceeded even my expectations. It was a true honor and pleasure to be a part of this research.”