Pokémon Go Data Powers New Mapping Technology

A decade after its release, the augmented reality game Pokémon Go is now contributing to a new generation of mapping technology used in robotics, built from billions of images submitted by players over time.

Originally released in 2016, Pokémon Go is a mobile game that uses augmented reality and location-based technology to place virtual creatures, known as Pokémon, into real-world settings. Players explore their surroundings using a smartphone, visiting parks, landmarks, and public spaces to catch Pokémon, battle at designated locations, and interact with in-game features tied to real-world geography. The game quickly became a global phenomenon, drawing millions of users outdoors and encouraging them to engage with physical locations in a new way.

According to a recent report, players have collectively generated more than 30 billion ground-level images by scanning landmarks, streets, and public locations while playing the game. These images have been compiled and processed by Niantic Spatial, a division focused on artificial intelligence and geospatial mapping, into a detailed digital model of real-world environments.

The system, known as a Visual Positioning System, uses images rather than traditional satellite signals to determine location. This approach allows for greater accuracy in dense urban areas, where GPS signals can be disrupted by buildings and other obstacles. By comparing live camera feeds to its database, the system can identify position and orientation in real time.

Niantic Spatial is now deploying this technology in partnership with Coco Robotics, a company that operates delivery robots in multiple cities. The robots use the image-based system to navigate sidewalks and deliver food and goods with improved precision, particularly in environments where GPS alone may be unreliable.

The underlying data was gathered through gameplay features that encouraged users to scan real-world locations, often as part of optional tasks tied to in-game rewards. Over time, repeated scans of the same areas from different angles, lighting conditions, and perspectives helped build a highly detailed and continuously updated map.

Developers say the technology addresses a longstanding challenge in robotics, often referred to as the “last-mile” problem, where precise navigation is required to reach a specific doorstep or location. Image-based positioning allows robots to operate more reliably in complex city environments where traditional navigation methods can fall short.

The project is part of a broader trend in which data collected for consumer applications is later adapted for use in artificial intelligence and automation. In this case, a mobile game that once encouraged users to explore their surroundings has contributed to a large-scale effort to model the physical world in detail, with applications extending beyond gaming into logistics and robotics.