{"id":353974,"date":"2026-03-19T07:50:07","date_gmt":"2026-03-19T07:50:07","guid":{"rendered":"https:\/\/www.newsbeep.com\/ie\/353974\/"},"modified":"2026-03-19T07:50:07","modified_gmt":"2026-03-19T07:50:07","slug":"pokemon-go-players-built-a-30-billion-photo-map-thats-now-training-robots-to-deliver-your-pizza","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ie\/353974\/","title":{"rendered":"Pok\u00e9mon Go players built a 30-billion-photo map that’s now training robots to deliver your pizza"},"content":{"rendered":"

Pikachus at every street corner. Leveling up before getting into the gym. \u201cPok\u00e9mon Go to the polls<\/a>.\u201d You remember this era well: Pok\u00e9mon Go became a frenzy<\/a>, with hundreds of millions taking to the streets<\/a> for their chance to snap up the rare Azelf or special edition Charizard. Now, not only does it seem that Pok\u00e9mon Go took the world by storm, but it also was using crowdsourced data to map it.<\/p>\n

Over the past decade, Pok\u00e9mon Go players voluntarily submitted photos and short videos of public landmarks, street corners, storefronts, and urban intersections\u2014all coming together to create a dataset that now stands at 30 billion images captured at ground level, across nearly every major city on the planet. Niantic Spatial, the enterprise AI and mapping division spun from Niantic Inc., has spent years converting that trove into something the robotics industry has never seen before: a photorealistic, street-level, continuously updated model of the physical world, built specifically for robots.<\/p>\n

That model is now being deployed to navigate Coco Robotics\u2019 roughly 1,000 delivery bot fleet operating in cities across the country and around the world, including Los Angeles, Chicago, Miami, Jersey City, and Helsinki, logging millions of miles of deliveries to date. Brian McClendon, Niantic Spatial\u2019s chief technology officer and one of the original creators of Google<\/a> Earth, explains the data strategy plainly. <\/p>\n

\u201cWe look at the player data as very high-quality ground training data for other lower-quality datasets,\u201d McClendon told Fortune in a statement. \u201cThe long-term philosophy of Niantic Spatial is that we can solve these hard problems of localization, reconstruction, and semantics by using very concentrated places to train models and then use much more broadly available data at lower resolution to be able to localize, visualize, and understand from \u2018bad\u2019 data.\u201d<\/p>\n

The 30 billion Pok\u00e9mon Go images aren\u2019t just a map: They are a master key that unlocks the potential of how to create a real-world, real-time map. The player scans teach the model what precision looks like\u2014it\u2019s so precise, in fact, that it can even signal when the input is imperfect. It\u2019s a strategy that positions Niantic Spatial less as a gaming company that pivoted and more as the most ambitious mapping operation ever assembled\u2014one that was funded entirely by its own users\u2019 enthusiasm for catching digital creatures.<\/p>\n

Niantic Spatial\u2019s Visual Positioning System, or VPS, solves a problem that has quietly stunted the autonomous delivery industry. GPS, the backbone of most navigation systems, doesn\u2019t fare that well in dense urban environments, where tall buildings interfere with satellite signals. For a delivery robot that needs to drop food at a precise doorstep, being several feet off means unhappy customers complaining their burger is cold\u2014or in their neighbor\u2019s tummy. Instead, the VPS bypasses satellites entirely, comparing live camera feeds from the robot against its vast image database to determine position in real time. <\/p>\n

\u201cThe model will work in real time, taking in images from the robot and comparing them to both publicly available as well as proprietary datasets we\u2019ve collected to determine the robot\u2019s global position and heading,\u201d a Niantic Spatial spokesperson told Fortune in a statement. The company knew where this tech performs best: \u201cNiantic Spatial\u2019s VPS is particularly resilient in urban canyons where GPS performs badly.\u201d<\/p>\n

\u201cOur initial VPS was built using scans that users choose to take in games\u2014but no single source defines the model,\u201d the Niantic Spatial spokesperson said. Player participation was always opt-in: users had to actively choose to submit a short video scan of a specific public landmark. Today, the model increasingly learns from the data Niantic Spatial\u2019s enterprise customers generate themselves. The underlying engine\u2014a large geospatial model, or LGM, trained on billions of posed images and hundreds of millions of real-world scans\u2014powers three capabilities: reconstructing spaces as navigable 3D models, localizing machines within those spaces, and understanding environments semantically. As CEO John Hanke wrote in a recent blog<\/a> post: \u201cFor the past several years, we\u2019ve been building a large geospatial model that acts as a living, breathing map of the world, one that is native to robots and AI.\u201d<\/p>\n

For Coco CEO Zach Rash, the problem is with robots\u2019 critical thinking skills (or lack thereof). <\/p>\n

\u201cRobots don\u2019t have the same intuition yet as a human, where a human can understand, \u2018My GPS isn\u2019t really working, but I understand that\u2019s probably the right place to go,’\u201d Rash told Fortune. \u201cWe need the robot to have that sort of intuition.\u201d<\/p>\n

\u201cWhen we go into really dense areas with high rises, that\u2019s where the VPS solution can be really helpful,\u201d Rash said. \u201cOur GPS and our existing solutions might fail in that sort of environment.\u201d <\/p>\n

The stakes, he noted, are felt by customers at the very last moment of a delivery: \u201cIt is a terrible customer experience if the robot parks in the wrong place waiting to receive that order.\u201d<\/p>\n

\u201cIt\u2019s very early with [Niantic Spatial], and I think we\u2019re excited to collaborate with such an incredible team on figuring out how we add this toward existing technology to make the service better. VPS is an obvious one,\u201d Rash continued. \u201cThey\u2019re very good at doing this. If I can more precisely figure out where to drop off food, my customers will be happy.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"Pikachus at every street corner. Leveling up before getting into the gym. \u201cPok\u00e9mon Go to the polls.\u201d You…\n","protected":false},"author":2,"featured_media":353975,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[61,60,5702,80,14799],"class_list":["post-353974","post","type-post","status-publish","format-standard","has-post-thumbnail","category-technology","tag-ie","tag-ireland","tag-privacy","tag-technology","tag-video-games"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/353974","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/comments?post=353974"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/353974\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media\/353975"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media?parent=353974"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/categories?post=353974"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/tags?post=353974"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}