Indoor AR navigation using visual localization technology
When GPS cannot be reached
We can see our location just by turning on a navigation device or map app. We are used to this. This is thanks mostly to the GPS. But what about indoors? Verifying a location indoors with no GPS signal remains a troublesome task. This is a problem that can be solved with a guide service or an indoor self-driving robot. The technologies and infrastructure do exist. Let’s take a look at what technologies NAVER LABS is using to find solutions.
A technology where just a photo is enough to recognize a location
We have raised the bar for visual localization (VL) technology. VL is a technology that determines a location using an image. In a way, this resembles our own daily experiences. People also view their surroundings with their eyes to identify where they are at any given moment. Of course, the scenery is a bit different from what people see. VL looks for distinct features in the image to identify positional information.
Visual localization demo
At NAVER LABS, we use the mapping robot M1. We extract distinct features from the data filmed by M1 to produce a “features map.” Information used for calculating a position is also included in this map. Using this feature map, positioning services can be performed with just one picture taken on a smartphone.
The error is much smaller when compared with GPS. Not only that, but it can even accurately measure the direction you’re facing.
Uninterrupted positioning is also important
We know that the current indoor position can be identified using VL technology. But neither people nor robots just stand still in one place all the time. They move around. Naturally, a precision positioning technology for situations involving movement is crucial.
The technology used for this scenario is Visual Intertial Odometry (VIO), which analyzes sensor and video data to track a position. This technology also incorporates the use of an optimization algorithm. This is to enable uninterrupted positioning in real time on a smartphone even with a limited network connection and a low-performance camera.
Comparison: (from left) VL alone → VL + VIO → VL + VIO + optimization algorithm
Essentially, VL technology tracks one’s current location, and when in motion the real-time position is tracked using VIO with applied optimization engineering. These positioning technologies are used in the Indoor AR Navigation and Indoor Self-driving Robot developed by NAVER LABS.
There is one more positioning technology that is useful for Indoor AR Navigation. It is Visual Object Tracking (VOT). This is a technology that can estimate the position or direction of a moving object by 6DoF (six degrees of freedom: forward, back, up, down, left, right) using image recognition technology. In an environment where VL does not function properly or is inaccurate, VOT is used to identify the exact location of an object or add content for specific areas.
VOT (visual object tracking) demo
The starting point of indoor location-based services: positioning
The core context of location-based services is, quite obviously, location. That is why when we say we’re solving the problem of positioning indoors where GPS doesn’t function, it also means that we’re promoting the birth of new services that we have never been able to experience indoors.
No longer will we have to struggle to find our way around a big department store when we go for the first time, and robots will also be able to provide services while planning and following routes on their own. AR, expanding space itself as an interface, can also lead to more varied and useful services based on user location. This is the motivation behind our continued research on indoor positioning technologies.