An autonomous desk tennis robotic developed by Sony AI has competed towards and defeated high-level human gamers in regulated matches, based on Reuters. The system is a part of a broader class sometimes called “physical AI,” the place synthetic intelligence is utilized to machines working in real-world environments.
The robotic, named Ace, was designed to function in a aggressive sport surroundings that requires speedy decision-making and exact motor management. In keeping with the undertaking crew, it combines high-speed notion methods with AI-driven management to execute photographs underneath match circumstances.
Ace competed in matches carried out underneath Worldwide Desk Tennis Federation guidelines and officiated by licensed umpires. In trials documented in April 2025, the system received three out of 5 matches towards elite gamers and misplaced two towards professional-level opponents. Sony AI reported that subsequent matches in December 2025 and early 2026 included wins towards skilled gamers.
Earlier desk tennis robots have existed because the Nineteen Eighties, however they weren’t in a position to match the efficiency of superior human gamers. “Not like laptop video games, the place prior AI methods surpass human specialists, bodily and real-time sports activities like desk tennis stay a significant open problem,” stated Peter DĂĽrr, director at Sony AI Zurich and lead of the undertaking.
AI methods have achieved sturdy ends in digital environments like chess and video video games, the place circumstances are totally simulated, DĂĽrr stated.
DĂĽrr stated the system was developed to check how robots can reply with velocity and accuracy in dynamic environments. The work was detailed in a examine printed within the journal Nature.
The game presents technical challenges because of the velocity and variability of the ball, together with advanced spin and altering trajectories, which require speedy sensing and coordinated motion in tight time constraints, DĂĽrr stated. Ace’s structure consists of 9 synchronised cameras and three imaginative and prescient methods, which observe the ball’s motion and spin. The system processes visible knowledge at a velocity adequate to seize movement that’s troublesome for the human eye to resolve. “That is quick sufficient to seize movement that may be a blur to the human eye,” DĂĽrr stated.
The robotic platform makes use of eight joints to manage the racket. Three management positioning, two management orientation, and three handle shot drive and velocity. The configuration was designed to satisfy the minimal mechanical necessities for aggressive play.
Not like many AI methods skilled by means of human demonstration, Ace was skilled in simulation. The method allowed it to develop its personal methods, leading to play patterns that differ from human opponents. Dürr stated the system “learns to play not from watching people” however by means of self-training in simulated environments.
Skilled participant Mayuka Taira, who misplaced a match to the system, stated the robotic was troublesome to foretell as a result of it exhibits no seen cues throughout play. Rui Takenaka, an elite participant who each received and misplaced towards Ace, stated it dealt with advanced spins effectively however was extra predictable on easier serves. Taira stated the system’s lack of emotional indicators made it tougher to anticipate its responses. “As a result of you’ll be able to’t learn its reactions, it’s unimaginable to sense what sort of photographs it dislikes or struggles with,” she stated.
DĂĽrr stated the system demonstrates sturdy capability in studying ball spin and reacting rapidly, whereas ongoing work focuses on enhancing adaptability throughout matches. The undertaking crew stated related notion and management strategies might be utilized to areas like manufacturing and repair robotics.
Humanoid robots examined in long-distance race
On the 2026 Beijing E-City Humanoid Robotic Half Marathon, humanoid robots competed over a 21-kilometre course in Beijing. The occasion included greater than 100 robots and roughly 12,000 human members, who ran on separate tracks.
A robotic named Lightning, developed by Honor, accomplished the race in 50 minutes and 26 seconds. The time was sooner than Olympic runner Jacob Kiplimo’s 57 minutes and 20 seconds recorded on the Lisbon Half Marathon in March. Lightning collided with a barricade through the race however continued and completed first. Honor robots additionally positioned second and third within the competitors. Efficiency improved in comparison with the earlier 12 months’s occasion, the place the quickest robotic accomplished the course in two hours, 40 minutes and 42 seconds. Organisers stated the occasion was meant to check humanoid robots in large-scale, real-world circumstances.
In keeping with Related Press, one other Honor robotic accomplished the course in 48 minutes underneath distant management. Nonetheless, race guidelines prioritised autonomous navigation, and Lightning was recognised because the official winner.
Honor engineers stated applied sciences developed for the robotic, together with structural reliability and liquid-cooling methods, might be utilized in industrial situations.
(Picture by Mattias Banguese)
See additionally: Cadence expands AI and robotic partnerships with Nvidia, Google Cloud
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