Boston Dynamics has deployed its Atlas and Spot robots at FIFA World Cup venues to showcase new AI capabilities and support security. Atlas learned to perform a complex soccer trick using reinforcement learning, a technique that trains robots in simulation before deploying to the physical world. Spot robots patrol stadiums to detect hazards and suspicious packages, marking a shift from industrial behind-the-scenes work to public-facing security roles.
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Boston Dynamics has taught its Atlas humanoid robot to perform the 'Ghost Rabona' soccer kick as part of Hyundai's partnership with FIFA World Cup. Spot quadrupeds are deployed at two stadiums in Dallas and two at Citi Field to support security operations by patrolling for hazards and suspicious packages.
Why it matters
The company shifted from classical predictive control to reinforcement learning (a machine-learning technique that lets robots learn behaviors in simulation), allowing Atlas to master complex interactions with objects and terrain that would be harder to program manually. The same techniques enabling Atlas to carry a fridge are now being applied to industrial warehouse tasks. For stadium operators, Spot provides autonomous or remote-controlled inspection without facial-recognition capability, complementing human security teams.
What to watch
The company emphasized that Atlas is far from matching human soccer players—it cannot yet interact safely with other people or run beside them. Spot is designed as a working tool for data collection and hazard detection, not a public spectacle; security teams themselves operate the robots in both autonomous and teleoperated modes.
Boston Dynamics' World Cup partnership marks a shift in how the company demonstrates its robots' capabilities and where they operate. Rather than competing in robot sports leagues, Hyundai is using the global platform to show Atlas and Spot performing real work—athletic tricks that require interaction with objects and terrain, and security patrols in crowded public venues. The technical foundation for this pivot is reinforcement learning, a machine-learning approach that trains robots in simulation by rewarding desired behaviors rather than programming each motion by hand. This method proved faster and more robust: the Ghost Rabona kick took only hours to a day to train, compared to the months of manual engineering that earlier techniques would have required. Critically, the same algorithms now enable Atlas to handle tasks like carrying a fridge, suggesting the company sees these showcase moments as proof-of-concept for industrial applications.
The deployment of Spot at stadium security represents a practical expansion beyond industrial settings (mines, nuclear facilities, warehouses). By having security teams operate the robots themselves rather than relying on specialists, Boston Dynamics is testing whether legged robots can integrate into existing workplace routines. The company was careful to note that Spot does not have facial-recognition capability, addressing privacy concerns head-on. However, Boston Dynamics also stressed that Atlas remains far from human soccer performance—it cannot yet safely interact with or move alongside people. This transparency suggests the company is managing expectations while building public familiarity with robots in everyday environments, a precondition for broader commercial adoption.
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