Augmented Reality SDK Frameworks

Top 5 Augmented Reality SDK Frameworks That You Should Prefer in Upcoming Year

AR becomes more and more popular currently although many people think it is still beyond to reach. But, this myth has changed with the development of a new range of AR apps. And if you’re going to get into AR, you must first choose an Augmented Reality SDK Frameworks.

This is not only a starting process but a first and important step for your Augmented Reality project. So, it is crucial that you pick carefully.

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While working on some of our recent AR projects, we wind-up that to pick an SDK or Framework while developing Augmented Reality application is not as easy as we thought. Each of the AR SDK differs from other by their some specific features.

Here’s providing you a detailed overview of Top 5 Augmented Reality SDK frameworks that are most commonly used among the AR Mobile App developers, which can help you to pick the right one.


Supported platforms: Android, iOS, Linux, Windows, Mac OS and Smart Glasses.

Pricing: Free, open source.

ARToolkit is the world’s most widely used open-source tracking library for creation of augmented reality apps. It uses video tracking capabilities to solve the problems such as viewpoint tracking and virtual object interaction.


  • Orientation tracking
  • 2D recognition
  • Easy calibration for new devices
  • Automatic camera calibration utilities
  • Square marker generation
  • Natural feature marker generation utilities

It supports various platforms: Android, MS Windows, Linux, iOS, Mac OS X, SGI and is also available as plugins for the Unity game engine. It’s an open-source SDK, so it provides a free development environment for all the mentioned platforms.


Supported platforms: Android, iOS, UWP and Unity Editor.

Pricing: Paid

With some of the exciting features, Vuforia SDK works well with iOS and Android platform and also enabling the development of AR applications in Unity.

Vuforia supports:

  • Target tracking
  • Multi-target detection
  • Virtual Buttons
  • Frame marker
  • 2D and 3D target recognition
  • Runtime image target selection
  • Extended tracking
  • Smart Terrain TM
  • Detection of multiple sorts of targets (e.g. objects, images, English text)

It also allows apps to use databases that are either on a local source or cloud for image recognition purpose.  There is also a separate version SDK for smart glasses that are currently traversing to its beta phase and is early accessible for applications created by qualified developers.


Supported platforms: Android, iOS, Windows for tablets, Smart Glasses.

Pricing: Paid

Wikitude SDK supports:

  • Image recognition and tracking
  • 3D model rendering and animation
  • Video overlay
  • Location-based tracking (image, text, button, and video)
  • HTML augmentation

This SDK is compatible with Android and iOS operating systems, Google Glass, Epson Moverio, Vuzix M-100 and Optinvent ORA1. It is also available as a module for Titanium, the plugin for PhoneGap and a constituent for Xamarin.

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The trial version of SDK is freely available for developers. If they want to continue with the complete version, they have to pay for it.


Supported platforms: Android, iOS

ARLab SDK is compatible with both Android and iOS operating systems. It offers amazing features like:

  • AR Browser
  • Image matching
  • Image tracking
  • Object tracking
  • Virtual Buttons
  • 3D engine

AR Browser SDK allows you to add and remove POIs from the pool independently from the picture in real time. With Image matching SDK you can create your own matching pool having thousands of images so that you can match multiple images without an internet connection and also supports barcode and QR code detection. Image tracking, Object tracking, and Virtual Button SDKs are available very soon.


Supported platforms: Android, iOS

DroidAR is an open-source framework for AR on Android that adds location-based and marker-based functionality to android apps.

This framework can be used for many various scenarios. It offers wonderful features like:

  • Gesture detection
  • Marker detection
  • Support for static and animated 3D objects
  • GPS
  • IMU sensors

But it is shaded by the poor documentation. There is also an individual section on project README file on GitHub that gives an overview of the closed-source version of DroidAR and DroidAR 2.


It’s imperative that you select the tool very carefully, which suits your project requirement and come up with an amazing new AR app. Hopefully, this article will help you through the first step of selection of AR framework for the development of AR apps. We’d love to know if you use any of the above-mentioned tools to integrate AR in your won app.

Put your comments below and share your experience with us.

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Chetan Sheladiya

Chetan Sheladiya

CEO at Metizsoft Solutions, a leading mobile apps development company, Chetan Sheladiya is a techie who loves to blog. Being passionate about new technology and how it emerged from its old counterpart, is what keeps Manthan interested the most. Blogging is a way for him to share his knowledge with other technology lovers like him!

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