top of page


The ArconaCore framework comprises several intermediate-level units: recognition, navigation, and SLAM. These units share a common property: scalability. They function effectively on both modest mobile devices and powerful platforms such as remote servers. 


Recognition: Our developed recognition approach boasts capabilities comparable to neural-network-based solutions. However, unlike the latter, all processing steps are implemented algorithmically. Consequently, the total number of operations performed is significantly reduced. As a result, recognition achieves satisfactory performance using only the mobile CPU, freeing up the mobile device’s GPU for high-resolution AR content rendering and related tasks


Navigation: The navigation unit geopositions a mobile device by performing bundle adjustment using information from various sources: GPS, Compass, Recognized spatial anchors, Odometry (SLAM) unit. The precision of positioning increases as more information is received from these sources.


SLAM (Simultaneous Localization and Mapping): Our SLAM unit combines the extended Kalman filter with a bundle adjustment approach. Importantly, this unit ensures our solutions remain independent of specific platforms like ArKit or ArCore.

In summary, ArconaCore’s modular design allows it to adapt seamlessly across different hardware configurations, making it a versatile choice for augmented reality applications. 


bottom of page