Why is our Wayfinding system unique?

    • NO GPS needed
    • SLAM based
    • Indoor and outdoor
    • Very accurate
    • Augmented ready
    • Unlimited POI’s
    • 3 Dimensional
    • Intelligent
    • BLE supported
    • Already in our phones

Location based applications

Our Visual SLAM technology empowers devices to find the location of any given object with reference to its surroundings and map the environmental layout with only one RGB camera. Our technology allows phones and tablets to instantly track the world around them and overlay digital elements. We use normally GPS applications such as Google Maps to find and get directions to any location and even get personalized data for driving, walking or public Transport. But this GPS technology has its limitations: low precision (~ few meters), the fact that it works only outdoors and poor signal reception in cities with tall buildings due to “urban canyon” effect.
This is not the case with our technology because it helps devices navigate spaces without prior reference points. The potential is resulting in investment – according to a market research report by BIS Research, the Visual SLAM technology market was estimated at $50 million in 2017 and is estimated to reach $8.23 billion by 2027.

Proof of concept

As a precursor to our SLAM based wayfinding system, XTEND developed and tested equivalent systems for the Museum of Cultural History (University Of Oslo). This resulted in three successful projects that made it possible for the Museum of Cultural History to test and evaluate the use of new interactive ways for the visitors to experience artefacts in the new Viking Age Museum (2025). We used Trained Model Target Datasets and this means that we used datasets to enable our applications to automatically switch between different objects and/or different Guide Views for each object, depending on what the user points their device at.

In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms work by making data-driven predictions or decisions, through building a mathematical model from input data.
The data used to build the final model usually comes from multiple datasets. In particular, three data sets are commonly used in different stages of the creation of the model. The model is initially fit on a training dataset, that is a set of examples used to fit the parameters of the model. Go to http://arim.tech for more info or watch one of our videos to see it working: https://vimeo.com/325846728


High-level functionality

For our AR development we use the AR Foundation package to add high-level functionality to augmented reality and it allows us to work in a multi-platform way.This allows us to develop our app once, then deploy it across multiple mobile and wearable AR devices. It includes core features from each platform, as well as unique Unity features that include photorealistic rendering, physics, device optimizations, and more.

industry-leading development

Unity’s real-time 3D development platform empowers us with all we need to create, operate, and monetize.This industry-leading development platform gives our developers the power to create games and applications that deliver on the promise of XR: apps that react to, and live in, the real world.
 
As we write software for XR, we need to develop systems that support continually changing requirements due to the pace at which innovation is happening.

AR Foundation supports the following concepts:

  • World tracking: track the device's position and orientation in physical space.
  • Plane detection: detect horizontal and vertical surfaces.
  • Point clouds, also known as feature points.
  • Reference points: an arbitrary position and orientation that the device tracks.
  • Light estimation: estimates for average color temperature and brightness in physical space.
  • Environment probes: a means for generating a cube map to represent a particular area of the physical environment.
  • Face tracking: detect and track human faces.
  • Image tracking: detect and track 2D images.
  • Object tracking: detect 3D objects.

Strategy

User-experience design

User-interface design

Development & interation

Deployment

Monitoring

 Gaustadalleen 21, 0349 Oslo
Bjørnemyrveien 11, 1453 Bjørnemyr