Visual SLAM algorithms and their application for AR, mapping, localization and wayfinding
Charalambos Theodorou,
Vladan Velisavljevic,
Vladimir Dyo,
Fredi Nonyelu
Affiliations
Charalambos Theodorou
School of Computer Science and Technology, University of Bedforshire, Luton, LU1 3JU, United Kingdom; Briteyellow Ltd, Bedford, MK43 0BT, United Kingdom; Corresponding author. School of Computer Science and Technology, University of Bedforshire, Luton, LU1 3JU, United Kingdom.
Vladan Velisavljevic
School of Computer Science and Technology, University of Bedforshire, Luton, LU1 3JU, United Kingdom
Vladimir Dyo
School of Computer Science and Technology, University of Bedforshire, Luton, LU1 3JU, United Kingdom
Fredi Nonyelu
Briteyellow Ltd, Bedford, MK43 0BT, United Kingdom
Visual simultaneous localization and mapping (vSLAM) algorithms use device camera to estimate agent's position and reconstruct structures in an unknown environment. As an essential part of augmented reality (AR) experience, vSLAM enhances the real-world environment through the addition of virtual objects, based on localization (location) and environment structure (mapping). From both technical and historical perspectives, this paper categorizes and summarizes some of the most recent visual SLAM algorithms proposed in research communities, while also discussing their applications in augmented reality, mapping, navigation, and localization.
