A team of researchers at ETH Zurich has introduced a new breakthrough in robotics and artificial intelligence—a four-legged robot capable of playing badminton rallies with humans. Known as ANYmal, the robot combines machine learning, real-time tracking, and high-speed motion control to engage in this fast-paced sport.
Merging Robotics with Sport
ANYmal, originally designed for industrial and exploration purposes, has been reprogrammed to take on the challenge of playing badminton—a sport that demands agility, precision, and split-second decision-making. Outfitted with a robotic arm and powered by advanced AI algorithms, the robot can detect shuttlecock trajectories, adjust its stance, and return shots in real time.
The project demonstrates how robotics can evolve from static automation to dynamic, interactive systems. According to the researchers, the goal wasn’t just to mimic human movement but to create a robotic system that can react strategically within a complex, ever-changing environment.
How It Works
The badminton-playing robot uses a combination of computer vision and deep learning to anticipate the shuttle’s path. Its sensors track the incoming shuttlecock and calculate the optimal strike position. The AI engine then guides its robotic arm to swing the racket with the appropriate force and angle.
ANYmal’s four-legged design gives it mobility and balance, helping it reposition quickly across the court. The robot is also trained using reinforcement learning techniques, where it improves through continuous trial and error.
Broader Implications of the Research
While playing badminton may seem like a novelty, the technology behind ANYmal has broader applications. The ability to process visual data and respond in real time could be applied in fields such as warehouse automation, search-and-rescue operations, and physical rehabilitation support.
It also offers a glimpse into the future of human-robot collaboration. As robots become more interactive and physically capable, they could be used not just for labor-intensive tasks, but also in education, sports training, and entertainment.
A New Dimension in AI-Driven Robotics
This development adds to the growing list of examples where AI and robotics intersect to push boundaries. By training a machine to not just perform actions but also anticipate and react like a human opponent, ETH Zurich is advancing the dialogue around intelligent, adaptable robotics.
With further refinement, systems like ANYmal could be used in training scenarios, competitive environments, or even as co-op partners in physical activities. The demonstration proves that AI isn’t just about text or speech—it’s about movement, intuition, and real-time interaction.