A woman holds up her cell phone as she plays the Pokémon Go game in Lafayette Park in front of the White House in Washington, DC on July 12, 2016. Jim Watson/AFP via Getty Images

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Nearly a decade ago, Pokémon Go turned the real world into a digital scavenger hunt, with virtual creatures hiding in plain sight. The early augmented reality smartphone app prompted hundreds of millions of players to wander into parks, parking lots, and even dimly lit alleyways, peering through their phone cameras in search of Pikachus and Charizards that the app superimposed onto their surroundings. It was a major hit. But 10 years on from the app’s peak, it turns out that digital creature catching may now help that piping hot pizza you ordered find you.

This week, Niantic Spatial, part of the team behind Pokémon Go, announced a partnership with Coco Robotics, a company that makes short-distance delivery robots for food and groceries. Soon, those robot couriers will scoot around sidewalks using Niantic’s Visual Positioning System (VPS)—a navigation tool that can reportedly pinpoint location down to a few centimeters just by looking at nearby buildings and landmarks. Niantic trained that VPS model on more than 30 billion images captured by Pokémon Go users, and claims it will help robots operate in areas where GPS falls short.

In other words, all that time users spent wandering around playing Pokémon Go will now help determine how well a courier robot can deliver your take out. It’s a stark example of how crowdsourced data, seemingly collected for one purpose, can be quietly repurposed years later for something quite different.

“It turns out that getting Pikachu to realistically run around and getting Coco’s robot to safely and accurately move through the world is actually the same problem,” Niantic Spatial CEO John Hanke said in a recent interview with MIT Technology Review. 

How Niantic repackages Pokémon Go data 

Instead of helping users navigate the way that GPS does, VPS determines where someone is based on their surroundings. That makes Pokémon Go particularly useful as a data source, because players had to physically travel to specific locations and point their phones at various angles. That mapping effort got a significant boost in 2020, when the app added what it called “Field Research,” a feature prompting players to scan real-world statues and landmarks with their cameras in exchange for in-game rewards. A portion of the data also reportedly came from areas known as “Pokémon battle arenas.” 

Whether players knew it or not, those scans were creating 3D models of the real world that would eventually power the Niantic model. More data means better accuracy, and because Niantic was collecting images of the same locations from many different users, it could capture the same spots across varying weather conditions, lighting, angles, and heights. There’s no shortage of raw material to draw from either. At its peak in 2016, Pokémon Go had around 230 million monthly active players. Though less culturally relevant in 2026, the game still hovers around 50 million active users by some estimates.

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How Pokémon Go data could help robots find their way

Niantic and Coco are betting that Pokémon Go data will help delivery robots understand precisely where they are simply by looking at landmarks around them. Though most autonomous robots currently use some form of GPS for navigation, it isn’t always reliable. Other delivery robots tested on college campuses have been known to get lost or struggle to cross streets. That confusion can lead to delays. As any diner who has waited too long for a hot meal from a delivery app can attest, it’s crucial these couriers arrive on time. After all, time is money.

“The promise of last-mile robotics is immense, but the reality of navigating chaotic city streets is one of the hardest engineering challenges,” Hanke said in a statement.

And while most people associate spotty GPS with state parks or remote rural areas, reliability is also often compromised in the tall, densely packed buildings of a concrete jungle. All of those structures can interfere with signals, causing the location dot on a map to drift. The idea is that Coco’s robots can use VPS and four cameras mounted around the machine to get a far more precise read on their surroundings. In turn, the well-equipped robot will deliver food on time.

VPS uses four cameras to get a more precise reading of its surroundings. Image: Coco Robotics.

This also wouldn’t be the first time data freely scavenged by internet users for one purpose ended up powering something else entirely. Most famously, Google’s CAPTCHA tests, which ask users to click on images of bicycles or traffic lights to verify they are human, have come under scrutiny. Computer scientists have long speculated that the CAPTCHA tests have been used to help train AI vision models. More recently, law enforcement has allegedly accessed or purchased user-generated content from the consumer mapping tool Waze to assist police investigations. And while Niantic hasn’t suggested any plans to provide its VPS data to authorities, it’s not hard to see how a tool that can accurately pinpoint a location based on landmarks in a photograph could look enticing to law enforcement.

On a broader level, Niantic says its partnership with Coco Robotics is part of a longer-term effort to build a “living map” of the world that updates as new data becomes available. Once VPS-equipped delivery robots hit the streets, they will collect even more info that can be fed back into the model to bolster its accuracy further. This kind of continuous, real-world data collection is already central to how self-driving vehicle companies like Waymo and Tesla operate, and is a large part of why that technology has improved so significantly in recent years.

So, next time you see someone in a park trying to “catch ‘em all,” it’s quite possible the data gleaned from that scavenger hunt could play a key role in determining whether the pizzas of the future make it to their destinations on time.

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