ORB_SLAM2

I was in no way trying to undercut Apple's efforts, just stating what's written in their documentation [1], i.e they're currently only performing tracking with VIO as compared with Google's [2]. "Almost by default a robust VO system using some kind of sensor fusion does a form of relocalization but rarely loop closure." This is not true, Visual(Inertial) Odometry systems typically estimate "odometry" i.e frame to frame motion tracking hence the name, such as in [3] and [4], whereas SLAM systems, such as [5], store a map of features, and their descriptors to relocalize which isn't necessarily a typical feature of pure VO systems. [1] https://developer.apple.com/arkit [2] https://developers.google.com/tango/developer-overview [3] https://github.com/uzh-rpg/rpg_svo [4] https://github.com/ethz-asl/rovio [5] https://github.com/raulmur/ORB_SLAM

It seems that ARkit is actually using SLAM as the core technology (in parts, the same technology is being used in autonomous cars and navigating drones). Getting it to work on mobile phones is quite challenging and had been the subject of much research in recent years, some good starting points (with code): ORB-SLAM - https://github.com/raulmur/ORB_SLAM2, https://www.youtube.com/watch?v=T-9PYCKhDLM DSO - https://github.com/JakobEngel/dso, https://www.youtube.com/watch?v=C6-xwSOOdqQ VINS - https://github.com/HKUST-Aerial-Robotics/VINS-Mobile, https://www.youtube.com/watch?v=0mTXnIfFisI&feature=youtu.be (the last one being released just a few days ago...) Of course there are a lot more resources out there and a lot of the cutting edge research is involved with deep learning techniques (starting with e.g. https://github.com/alexgkendall/caff