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Tango (platform)
Tango (platform)
Tango (platform)
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Tango
Original authorGoogle
DeveloperGoogle
Initial releaseJune 5, 2014; 11 years ago (2014-06-05)
PlatformAndroid
Available inEnglish
TypeComputer vision
Websitedevelopers.google.com/tango/

Tango (named Project Tango while in testing) was an augmented reality computing platform, developed and authored by the Advanced Technology and Projects (ATAP), a skunkworks division of Google. It used computer vision to enable mobile devices, such as smartphones and tablets, to detect their position relative to the world around them without using GPS or other external signals. This allowed application developers to create user experiences that include indoor navigation, 3D mapping, physical space measurement, environmental recognition, augmented reality, and windows into a virtual world.

The first product to emerge from ATAP,[1] Tango was developed by a team led by computer scientist Johnny Lee, a core contributor to Microsoft's Kinect. In an interview in June 2015, Lee said, "We're developing the hardware and software technologies to help everything and everyone understand precisely where they are, anywhere."[2]

Google produced two devices to demonstrate the Tango technology: the Peanut phone and the Yellowstone 7-inch tablet. More than 3,000 of these devices had been sold as of June 2015,[3] chiefly to researchers and software developers interested in building applications for the platform. In the summer of 2015, Qualcomm and Intel both announced that they were developing Tango reference devices as models for device manufacturers who use their mobile chipsets.[4][5]

At CES, in January 2016, Google announced a partnership with Lenovo to release a consumer smartphone during the summer of 2016 to feature Tango technology marketed at consumers, noting a less than $500 price-point and a small form factor below 6.5 inches. At the same time, both companies also announced an application incubator to get applications developed to be on the device on launch.

On 15 December 2017, Google announced that they would be ending support for Tango on March 1, 2018, in favor of ARCore.[6]

Overview

[edit]

Tango was different from other contemporary 3D-sensing computer vision products, in that it was designed to run on a standalone mobile phone or tablet and was chiefly concerned with determining the device's position and orientation within the environment.

The software worked by integrating three types of functionality:

  • Motion-tracking: using visual features of the environment, in combination with accelerometer and gyroscope data, to closely track the device's movements in space
  • Area learning: storing environment data in a map that can be re-used later, shared with other Tango devices, and enhanced with metadata such as notes, instructions, or points of interest
  • Depth perception: detecting distances, sizes, and surfaces in the environment

Together, these generate data about the device in "six degrees of freedom" (3 axes of orientation plus 3 axes of position) and detailed three-dimensional information about the environment.

Project Tango was also the first project to graduate from Google X in 2012 [7]

Applications on mobile devices use Tango's C and Java APIs to access this data in real time. In addition, an API was also provided for integrating Tango with the Unity game engine; this enabled the conversion or creation of games that allow the user to interact and navigate in the game space by moving and rotating a Tango device in real space. These APIs were documented on the Google developer website.[8]

Applications

[edit]

Tango enabled apps to track a device's position and orientation within a detailed 3D environment, and to recognize known environments. This allowed the creations of applications such as in-store navigation, visual measurement and mapping utilities, presentation and design tools,[9] and a variety of immersive games. At Augmented World Expo 2015,[10] Johnny Lee demonstrated a construction game that builds a virtual structure in real space, an AR showroom app that allows users to view a full-size virtual automobile and customize its features, a hybrid Nerf gun with mounted Tango screen for dodging and shooting AR monsters superimposed on reality, and a multiplayer VR app that lets multiple players converse in a virtual space where their avatar movements match their real-life movements.[11]

Tango apps are distributed through Play. Google has encouraged the development of more apps with hackathons, an app contest, and promotional discounts on the development tablet.[12]

Devices

[edit]

As a platform for software developers and a model for device manufacturers, Google created two Tango devices.

The Peanut phone

[edit]

"Peanut" was the first production Tango device, released in the first quarter of 2014. It was a small Android phone with a Qualcomm MSM8974 quad-core processor and additional special hardware including a fisheye motion camera, "RGB-IR" camera for color image and infrared depth detection, and Movidius Vision processing units. A high-performance accelerometer and gyroscope were added after testing several competing models in the MARS lab at the University of Minnesota.

Several hundred Peanut devices were distributed to early-access partners including university researchers in computer vision and robotics, as well as application developers and technology startups. Google stopped supporting the Peanut device in September 2015, as by then the Tango software stack had evolved beyond the versions of Android that run on the device.

The Yellowstone tablet

[edit]
Google's Project Tango tablet, 2014

"Yellowstone" was a 7-inch tablet with full Tango functionality, released in June 2014, and sold as the Project Tango Tablet Development Kit.[13] It featured a 2.3 GHz quad-core Nvidia Tegra K1 processor, 128GB flash memory, 1920x1200-pixel touchscreen, 4MP color camera, fisheye-lens (motion-tracking) camera, an IR projector with RGB-IR camera for integrated depth sensing, and 4G LTE connectivity.[14][15] As of May 27, 2017, the Tango tablet is considered officially unsupported by Google.[16]

Testing by NASA

[edit]

In May 2014, two Peanut phones were delivered to the International Space Station to be part of a NASA project to develop autonomous robots that navigate in a variety of environments, including outer space. The soccer-ball-sized, 18-sided polyhedral SPHERES robots were developed at the NASA Ames Research Center, adjacent to the Google campus in Mountain View, California. Andres Martinez, SPHERES manager at NASA, said "We are researching how effective [Tango's] vision-based navigation abilities are for performing localization and navigation of a mobile free flyer on ISS.[17]

Intel RealSense smartphone

[edit]

Announced at Intel's Developer Forum in August 2015,[18] and offered to public through a Developer Kit since January 2016.[19] It incorporated a RealSense ZR300 camera[20] which had optical features required for Tango, such as the fisheye camera.[21]

Lenovo Phab 2 Pro

[edit]

Lenovo Phab 2 Pro was the first commercial smartphone with the Tango Technology, the device was announced at the beginning of 2016, launched in August, and available for purchase in the US in November. The Phab 2 Pro had a 6.4 inch screen, a Snapdragon 652 processor, and 64 GB of internal storage, with a rear facing 16 Megapixels camera and 8 MP front camera.

Asus Zenfone AR

[edit]

Asus Zenfone AR, announced at CES 2017,[22] was the second commercial smartphone with the Tango Technology. It ran Tango AR & Daydream VR on Snapdragon 821, with 6GB or 8GB of RAM and 128 or 256GB of internal memory depending on the configuration.

See also

[edit]

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Tango (platform)

View on Grokipedia
from Grokipedia
Tango was an (AR) computing platform developed by , designed to equip mobile devices with the ability to perceive and map their surrounding environment in three dimensions using specialized sensors and algorithms. Initially announced in February 2014 as Project Tango by Google's Advanced Technology and Projects (ATAP) division, it sought to provide devices with a "human-scale understanding of space and motion," enabling features like indoor , 3D mapping, and interactive AR experiences without relying on GPS. The platform's core technology integrated hardware components such as a depth-sensing camera, a motion-tracking camera, and an time-of-flight , which collectively captured over 250,000 measurements per second to track device position, detect surfaces, and reconstruct environments in real time. This allowed for advanced capabilities including area learning—where devices could remember and revisit mapped spaces—and for overlaying virtual objects onto the physical world with precision. released developer kits starting in 2014, including a and later a tablet powered by K1, to foster app development for AR applications like gaming, , and spatial simulations. Consumer adoption was limited due to the need for custom hardware, with only a handful of compatible devices launched, such as the Phab 2 Pro in 2016 and the Asus ZenFone AR in 2017, both featuring Tango-enabled sensors for AR experiences. Despite demonstrations at events like 2014—showcasing interactive 3D games and virtual reconstructions—the platform struggled with high manufacturing costs and low , as manufacturers were reluctant to integrate the specialized components into mainstream phones. In December 2017, Google announced the discontinuation of , with official support ending on March 1, 2018, to redirect resources toward , a more accessible AR that leverages standard hardware like those in the and S8. built upon some of 's foundational technologies, such as plane detection and motion tracking, but expanded compatibility to over 100 million devices by prioritizing software-only solutions amid growing competition from Apple's ARKit. This shift marked 's legacy as a pioneering but hardware-intensive effort in mobile AR, influencing the evolution of immersive computing on Android platforms.

History and Development

Origins and Announcement

Project Tango was initiated by in early 2014 as an experimental platform aimed at advancing mobile (AR) through enhanced spatial awareness capabilities. Developed under the company's Advanced Technology and Projects (ATAP) group, a skunkworks division focused on innovative hardware and software prototypes, the project sought to equip smartphones and tablets with the ability to perceive and map their physical environment in three dimensions without relying on external markers or infrastructure. The platform was publicly announced on February 20, 2014, with Google unveiling a prototype 5-inch Android smartphone that incorporated custom sensors for real-time motion tracking and . This initial reveal highlighted Tango's potential to enable applications such as indoor , interactive 3D gaming, and environmental reconstruction, allowing devices to build persistent models of spaces like homes or offices for seamless AR overlays. To foster development, Google distributed approximately 200 units of this "Peanut" prototype to select external developers and researchers by March 2014, encouraging experimentation with the platform's APIs for position, orientation, and depth data. Google's motivations for Project Tango stemmed from a desire to replicate human-like spatial understanding on mobile devices, addressing limitations in traditional GPS for indoor and close-range scenarios. By combining algorithms with specialized hardware, the project aimed to support use cases like gesture-based interactions, virtual object placement, and collaborative mapping, ultimately democratizing 3D sensing for consumer and enterprise AR experiences. In the months following the announcement, formed early partnerships to expand Tango's reach, including collaborations with for potential consumer device integration and for testing prototypes on the to evaluate 3D mapping in microgravity environments. These initial alliances underscored ATAP's strategy of and cross-industry application testing.

Key Milestones

In June 2014, at , Google announced the Project Tango Tablet Development Kit, a 7-inch device powered by an K1 processor, priced at $1,024 and available to developers starting late that month. In 2015, Google expanded the availability of Project Tango tablet development kits to additional countries, including , , and several European nations, to broaden access for software developers exploring 3D motion tracking and environmental sensing. By August 2015, over 3,000 such developer devices had been shipped worldwide, fostering early experimentation with the platform's capabilities. In 2016, partnered with to integrate RealSense depth-sensing technology into a new Project Tango developer kit, enabling enhanced 3D mapping and for Android applications. This collaboration, announced at CES 2016, allowed developers to leverage RealSense SDK alongside the SDK for more accurate spatial awareness in mobile devices. Later that year, the PHAB 2 Pro became the first consumer-ready Tango-enabled device, released in November and featuring specialized cameras and sensors for experiences. Additionally, conducted testing of Project Tango technology aboard the in 2016, integrating it with SPHERES free-flying robots to improve localization through stereo vision and 3D mapping without relying solely on ultrasonic beacons. By 2017, Project Tango expanded to additional smartphones, including the Asus Zenfone AR, which launched in June as a high-end device supporting Tango's motion tracking and for immersive AR applications. The developer community saw significant growth that year, with over 100 apps available in the dedicated Tango section of the Store by mid-2017, including AR games like Measure and interactive tools for real-world object scanning.

Technical Overview

Core Technologies

The Tango platform relied on advanced algorithms to enable (AR) capabilities on mobile devices, primarily through three interconnected technologies: motion tracking, area learning, and . Motion tracking utilized the device's cameras, , and to determine its position and orientation in 3D space in real time, employing techniques to compare visual features like edges and corners without storing images or relying on external networks. This process formed the basis of Tango's (SLAM) implementation, which allowed for robust, drift-resistant tracking by continuously updating the device's pose relative to the environment. Area learning extended these capabilities by enabling devices to create and store persistent 3D models of indoor spaces, facilitating the reconstruction of environments across multiple sessions. Through , Tango captured visual features via the camera and combined them with location services to generate a compact mathematical index stored on-device, allowing quick recognition and alignment of previously mapped areas for consistent AR experiences. This feature supported persistent AR scenes, where virtual objects could be anchored to real-world locations and reloaded accurately over time, enhancing applications like indoor navigation and multi-user AR. Depth perception complemented motion tracking and area learning by providing precise distance measurements, essential for realistic AR interactions such as occlusion and object placement. Tango's algorithms processed data from infrared-based 3D sensors to generate depthmaps, measuring distances from 0.5 to 4 meters in indoor settings and enabling real-time 3D mapping of surroundings. These depth estimates were integrated into the SLAM pipeline to refine environmental models, ensuring virtual elements interacted naturally with physical geometry. The software stack powering these technologies centered on the SDK, which provided developers with for accessing motion tracking, area learning, and depth data. The SDK included a C-based Client API compatible with the Android Native Development Kit (NDK) for low-level integration, allowing custom implementations of pipelines. Additionally, a dedicated Unity plugin enabled seamless incorporation of Tango features into Unity-based AR applications, supporting real-time rendering and scripting for 3D mapping and SLAM-driven interactions. This architecture prioritized on-device processing to minimize latency, with all core algorithms running locally to deliver responsive AR without cloud dependency.

Hardware Requirements

The Tango platform mandated a suite of specialized sensors to deliver precise spatial awareness and augmented reality functionality. Central to this were inertial measurement units (IMUs), such as the InvenSense MPU-9150 or Bosch BMX055, which provided 9-axis motion data including gyroscope, accelerometer, and compass readings for real-time device orientation tracking. Complementing the IMU was a fisheye camera offering a 180-degree field of view, typically an OmniVision module, enabling wide-angle visual odometry to capture environmental features for robust pose estimation. For depth perception, devices incorporated either time-of-flight (ToF) or structured light sensors; the latter commonly featured an infrared projector emitting dot patterns alongside a 4 MP RGB-IR camera (e.g., OmniVision) and a PrimeSense PSX1200 Capri 3D sensor SoC to compute over 250,000 3D points per second. Minimum hardware specifications for Tango compatibility emphasized integration and performance to handle effectively. Supported devices required Android 5.0 or later as the operating system, at least 2 GB of LPDDR3 RAM to manage real-time processing demands, and seamless incorporation of the Tango SDK for aggregating data from the IMU, cameras, and depth sensors into a unified spatial model. These specs ensured the platform could perform continuous motion tracking and area learning without excessive latency, though early prototypes like the development tablet used a Snapdragon quad-core processor at up to 2.3 GHz to meet these thresholds. The reliance on custom hardware presented notable challenges, particularly in power consumption and cost, which hindered broader market adoption. The additional sensors and associated processing—such as projection and high-frame-rate depth computation—drew significant battery power, often reducing device runtime compared to standard smartphones and necessitating larger batteries that impacted form factor. Manufacturing costs escalated due to the integration of specialized components like the and IR arrays, with development kits priced around $1,024, making consumer devices like the Phab 2 Pro retail at $499 despite modest overall specs, thus limiting appeal to niche professional users rather than mass consumers. Accurate operation of Tango's AR features depended on rigorous processes to align outputs for reliable depth mapping and pose estimation. Initial factory synchronized the depth and RGB cameras' extrinsic parameters, compensating for misalignments in the structured light system to produce coherent 3D point clouds. Users performed ongoing calibrations via the Tango app, involving movements like figure-eight patterns to fuse IMU data with visual features from the fisheye camera, refining pose accuracy to sub-centimeter levels indoors. These steps mitigated drift in motion tracking algorithms and ensured precise environmental reconstruction, though environmental factors like lighting could necessitate recalibration for optimal performance.

Applications and Use Cases

Developer Tools

The Tango SDK offered developers a suite of centered on three primary components: the motion tracking API, the area learning API, and the depth API. The motion tracking API enabled precise 6-degrees-of-freedom (6DoF) positioning and orientation of the device in real-world space using visual-inertial , allowing applications to respond dynamically to user movement without external beacons. The area learning API facilitated the creation and storage of 3D spatial maps of environments, enabling persistent experiences where virtual elements could be anchored to specific locations even across app sessions or device restarts. The depth API provided access to depth data from sensors, supporting features like occlusion handling and environmental reconstruction for immersive interactions. Integration with development environments was streamlined to support both 3D-focused and native application building. For 3D apps, the SDK was compatible with Unity 5 and subsequent versions, including pre-built examples in the official Unity plugin that demonstrated API usage through scripts for scene rendering and interaction. Developers could also build native Android applications using , incorporating the SDK via or C/C++ bindings in the , with setup guides specifying compatible SDK versions like API level 24. Google released a variety of sample applications and to illustrate SDK capabilities, emphasizing practical AR implementations. The MeasureIt app, for instance, served as a tutorial example for using the depth and motion tracking to perform accurate distance measurements between points in a physical space, such as room dimensions. Virtual placement demos, like those in the "Virtual Cats" project, showcased the area learning API by allowing users to position and interact with 3D virtual objects—such as furniture or animated characters—in real environments, with covering anchoring, scaling, and . To foster adoption, provided community resources including official developer forums for troubleshooting and knowledge sharing, which operated until the platform's discontinuation. Additionally, hosted developer challenges, such as the 2015 Project Tango App Contest that encouraged innovative uses of the SDK and awarded submissions in categories like gaming and , with similar events and workshops continuing through 2016 and 2017 to promote collaborative experimentation.

Real-World Implementations

Tango's real-world implementations demonstrated its potential for immersive experiences across multiple sectors, leveraging its motion tracking and depth sensing capabilities to overlay digital content onto physical environments. In gaming, developers created interactive AR titles that transformed everyday spaces into play areas. For instance, Tango Village allowed users to explore virtual worlds by walking through mapped rooms, enabling multiplayer VR interactions where players could navigate shared environments in real time. Similarly, whimsical apps like placed virtual cats in users' homes, encouraging playful interactions as the animals responded to the device's spatial awareness. Other titles, such as zombie-shooting experiences, utilized Tango's 3D mapping to create dynamic combat scenarios tied to the user's physical surroundings, highlighting over two-thirds of Tango apps being games at the platform's peak. In enterprise applications, Tango facilitated practical tools for visualization and navigation in retail and logistics. WayfairView, an early AR app, let users virtually place furniture in their actual rooms by scanning spaces with Tango-enabled devices, serving as a precursor to broader adoption in apps like for accurate product scaling and placement with up to 98% precision in controlled settings. Retailers like integrated Tango for indoor , guiding shoppers to specific aisles and products through augmented overlays, while piloted it for personalized rewards via virtual store mapping. Educational and training uses leveraged Tango's area learning for interactive simulations. Google's AR Expeditions app brought historical sites and scientific concepts into classrooms, allowing students to walk through virtual reconstructions overlaid on real spaces using Tango devices. The Solar Simulator app enabled virtual tours of the solar system, scaling planetary models to user movements for understanding astronomical distances. In training contexts, architectural walkthroughs utilized Tango's 3D scanning for site reconnaissance, generating models of buildings for virtual inspections and design reviews. Despite these advancements, Tango implementations revealed key limitations tied to environmental factors. Accuracy heavily depended on consistent conditions, with excessive or insufficient illumination causing drifts and distorted 3D maps, as uniform was essential to minimize noise during scanning. Additionally, effective mapping required deliberate device movement to build area data, leading to instability in static or low-mobility scenarios, where virtual overlays could lag or misalign. These constraints often necessitated user training and controlled environments for reliable performance.

Supported Devices

Early Prototypes

The initial experimental prototypes for Google's Tango platform were designed to validate the core concept of embedding motion tracking, area learning, and capabilities directly into mobile hardware, serving as internal reference designs rather than consumer products. The first of these was "The Peanut," a compact Android smartphone prototype developed in early 2014 as Google's inaugural production device for Project Tango. Equipped with a Qualcomm Snapdragon 800 processor, it integrated specialized sensors including a fisheye wide-angle camera for 360-degree , an depth sensor, and enhanced (IMUs) to enable real-time 3D mapping and localization without relying on external infrastructure like GPS. This prototype allowed early testing of environmental understanding in handheld form factors, capturing up to 250,000 depth measurements per second to construct dynamic 3D models of surroundings. Building on the Peanut's foundation, Google introduced the "Yellowstone" tablet prototype in 2015, a 7-inch Android development kit optimized for broader developer experimentation with Tango's spatial awareness features. Unlike the phone-sized Peanut, Yellowstone adopted a larger form factor to accommodate bulkier sensor arrays, including a time-of-flight (ToF) depth camera for precise distance measurement and an (IR) projector from Mantis Vision to illuminate scenes for enhanced low-light performance. Powered by a Tegra K1 processor, it supported applications like indoor navigation and overlays, with over 3,000 units distributed to select developers for app prototyping. The tablet's design emphasized robustness for extended testing sessions, incorporating dual batteries for prolonged operation during complex tasks. A notable application of these prototypes emerged through a collaboration with , where the device was adapted for zero-gravity testing to explore Tango's potential in space environments. In 2014, partnered with 's to integrate the prototype onto SPHERES (Synchronized Position Hold, Engage, Reorient, Experimental Satellites) robots aboard the , enabling autonomous 3D mapping of habitats without gravity-dependent cues. This initiative demonstrated Tango's utility for simulations and real-time habitat documentation, with the prototypes undergoing parabolic flight tests to simulate microgravity conditions prior to ISS deployment. Despite their technical advancements, the early Tango prototypes faced significant limitations that confined them to research and development contexts. Both the Peanut and Yellowstone were prohibitively expensive, with the tablet development kit priced at around $1,024 for approved partners, reflecting the custom integration and low-volume production. Their bulkiness—exemplified by Yellowstone's 15.36 mm thickness and 370-gram weight—stemmed from the protruding IR projector and additional cameras, rendering them impractical for everyday consumer use and highlighting the challenges of miniaturizing advanced depth-sensing hardware. These prototypes prioritized proof-of-concept validation, including basic for combining visual and inertial data, over market viability.

Commercial Devices

The commercial rollout of Google's Project Tango was limited, with only a handful of consumer devices released between 2016 and 2017, primarily smartphones equipped with the specialized sensors required for Tango's augmented reality capabilities, such as motion-tracking cameras, depth sensors, and fisheye lenses. The Phab 2 Pro, launched in September 2016, marked the first consumer device to support . This 6.4-inch featured a 652 processor, a QHD display, and integrated Tango hardware enabling advanced AR experiences like spatial mapping and 3D object placement. Priced starting at $499, it was positioned as a premium option for early AR adopters, with availability in select markets including the through retailers like . In 2017, released the Zenfone AR, the second major Tango-enabled smartphone and the first to also support Google's Daydream VR platform. Featuring a 5.7-inch Super IPS+ display, Snapdragon 821 processor, and a 23-megapixel camera optimized for AR , it emphasized applications in gaming and creative imaging, such as overlaying virtual elements in real-world environments. Available in configurations from 4GB/32GB to 8GB/128GB storage, it launched at prices ranging from $599 to $699, making it a more compact alternative to the Phab 2 Pro while targeting enthusiasts in gaming and augmented . Lenovo also offered the Phab 2 Plus as a budget-oriented variant in its Phab 2 series, released alongside the Pro model in 2016 at a starting price of $299. While lacking the full suite of Tango sensors, it provided partial AR functionality through its dual 13-megapixel rear cameras, supporting basic effects like virtual backgrounds and manual imaging modes that hinted at AR potential without the depth perception and motion tracking of true Tango support. Despite these releases, Tango's commercial adoption faced significant challenges, with only two major devices entering the market amid high pricing above $500 for full-support models, which deterred widespread consumer interest and resulted in low sales volumes. The specialized hardware increased manufacturing costs, limiting partnerships to a few manufacturers and contributing to Tango's niche status before its transition to broader platforms like .

Discontinuation and Legacy

End of Support

On December 15, 2017, Google announced the end of support for the Tango platform, with the shutdown taking effect on March 1, 2018. The decision stemmed from several challenges, including a limited device ecosystem with fewer than 10 compatible models, such as the Lenovo Phab 2 Pro and Asus Zenfone AR, which restricted widespread adoption. High hardware barriers, requiring specialized sensors like depth cameras and motion trackers, further hindered scalability and accessibility for manufacturers and users. Additionally, developer feedback highlighted the platform's complexity in integration and deployment compared to emerging alternatives. Following the deadline, Tango-enabled applications ceased functioning on supported devices, as the underlying Tango Core service was discontinued, leaving no mechanism for AR processing. Users experienced immediate disruptions, with no further software updates, bug fixes, or technical assistance available from . Official downloads of the Tango SDK were terminated post-shutdown, preventing new development or redistribution through Google's channels. However, archived versions persisted on platforms like under Google's archive repository, allowing limited legacy access for existing projects. This marked the close of active maintenance, prompting a brief transition recommendation toward for ongoing AR efforts.

Transition to ARCore

Google launched ARCore in 2017 as a software-only platform designed to provide motion tracking capabilities using standard cameras and (IMUs), eliminating the need for the specialized hardware required by Tango. This shift allowed AR experiences to reach a wider audience without dedicated depth sensors or additional processors, focusing on compatibility with everyday Android devices. ARCore inherited key technologies from , particularly its simultaneous localization and mapping (SLAM) algorithms, which were adapted to function effectively on mainstream hardware for real-time environmental understanding and device positioning. These adaptations enabled broader device compatibility, with supporting over 100 distinct device models by 2018 through optimized visual-inertial odometry. The SLAM foundation from Tango allowed ARCore to track feature points in the camera feed while fusing IMU data, maintaining robust performance in varied lighting and motion conditions. ARCore introduced significant improvements over Tango, including drastically reduced hardware dependencies that extended support to mid-range smartphones, enhancing accessibility and performance efficiency on devices with standard specifications. By 2018, integrations like Cloud Anchors further advanced the platform by enabling shared AR experiences across devices via cloud-based anchoring, fostering collaborative applications without on-device limitations. Many developers building on migrated their applications to , leveraging the platform's expanded ecosystem, with providing resources and encouragement for this transition until the end of Tango support in 2018. This migration preserved Tango's innovative AR foundations while scaling them to millions of users, ensuring continuity for legacy projects in areas like spatial measurement and interactive overlays.

References

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  47. https://mashable.com/article/google-ar-expeditions
  48. https://developers.googleblog.com/travel-through-space-with-the-project-tango-app-solar-simulator/
  49. https://www.architectmagazine.com/technology/how-google-tango-and-makerbot-digitizer-could-change-architecture_o
  50. https://www.iaarc.org/publications/fulltext/ISARC2017-Paper121.pdf
  51. https://www.researchgate.net/publication/320292713_An_Investigation_of_Google_TangoR_Tablet_for_Low_Cost_3D_Scanning
  52. https://ed.ilogues.com/2016/02/03/capturing-scenes-with-the-project-tango-tablet
  53. https://dailywireless.org/mobile/what-happened-to-google-tango/
  54. https://www.youtube.com/watch?v=3BNOsxMZD14
  55. https://www.popsci.com/article/technology/experimental-google-smartphone-becomes-brain-space-robot/
  56. https://evertiq.com/design/35032
  57. https://www.cnet.com/reviews/google-project-tango-preview/
  58. http://projectango.wikidot.com/tango-specifications
  59. https://www.nasa.gov/news-release/project-tango-will-give-spheres-more-flying-capabilities/
  60. https://venturebeat.com/ai/googles-project-tango-3d-mapping-phones-are-headed-to-space-watch-this-zero-gravity-test
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  64. https://www.qualcomm.com/news/onq/2017/01/asus-zenfone-ar-worlds-first-snapdragon-821-powered-tango-enabled-smartphone
  65. https://www.cnet.com/pictures/asus-zenfone-ar/
  66. https://www.extremetech.com/mobile/260671-google-killing-tango-augmented-reality-platform
  67. https://www.engadget.com/2017-12-15-google-ends-tango-support-focus-arcore.html
  68. https://arstechnica.com/gadgets/2017/12/tango-down-googles-first-ar-project-officially-shuts-down-march-1/
  69. https://www.zdnet.com/article/google-shutting-down-project-tango-in-march-2018/
  70. https://stackoverflow.com/questions/49409799/where-can-i-download-google-tango-unity-package-at-2018
  71. https://blog.google/products/google-ar-vr/arcore-augmented-reality-android-scale/
  72. https://developers.google.com/ar/develop/fundamentals
  73. https://developers.google.com/ar/devices
  74. https://blog.google/products/google-ar-vr/arcore-developer-preview-2/
  75. https://9to5google.com/2018/12/07/arcore-1-6-rolling-out/
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