30-4: Semantic Simultaneous Localization and Mapping for Augmented Reality

2018 ◽  
Vol 49 (1) ◽  
pp. 391-394 ◽  
Author(s):  
Bing Yu ◽  
Yang Li ◽  
Chao Ping Chen ◽  
Nizamuddin Maitlo ◽  
Jiaqi Chen ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Simultaneous Localization And Mapping ◽  
Localization And Mapping

Simultaneous Localization and Mapping for Augmented Reality

2010 ◽  
Author(s):  
Gerhard Reitmayr ◽  
Tobias Langlotz ◽  
Daniel Wagner ◽  
Alessandro Mulloni ◽  
Gerhard Schall ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Simultaneous Localization And Mapping ◽  
Localization And Mapping

scholarly journals Visual SLAM Based Spatial Recognition and Visualization Method for Mobile AR Systems

2022 ◽  
Vol 5 (1) ◽  
pp. 11
Author(s):  
Jooeun Song ◽  
Joongjin Kook
Keyword(s):  
Machine Learning ◽  
Augmented Reality ◽  
Research And Development ◽  
Open Source ◽  
Simultaneous Localization And Mapping ◽  
Visualization Method ◽  
Visual Slam ◽  
Localization And Mapping ◽  
Mobile Ar ◽  
Spatial Recognition

The simultaneous localization and mapping (SLAM) market is growing rapidly with advances in Machine Learning, Drones, and Augmented Reality (AR) technologies. However, due to the absence of an open source-based SLAM library for developing AR content, most SLAM researchers are required to conduct their own research and development to customize SLAM. In this paper, we propose an open source-based Mobile Markerless AR System by building our own pipeline based on Visual SLAM. To implement the Mobile AR System of this paper, we use ORB-SLAM3 and Unity Engine and experiment with running our system in a real environment and confirming it in the Unity Engine’s Mobile Viewer. Through this experimentation, we can verify that the Unity Engine and the SLAM System are tightly integrated and communicate smoothly. In addition, we expect to accelerate the growth of SLAM technology through this research.

Simultaneous localization and mapping and the situativeness of a new generation of geomedia technologies

2019 ◽  
Vol 4 (2) ◽  
pp. 118-132
Author(s):  
Max Kanderske ◽  
Tristan Thielmann
Keyword(s):  
Augmented Reality ◽  
Simultaneous Localization And Mapping ◽  
Living Room ◽  
Interior Spaces ◽  
Localization And Mapping ◽  
Mapping Technology ◽  
Surrounding Space ◽  
The Moment ◽  
New Generation ◽  
Mathematical Construction

Simultaneous localization and mapping technology is commonly used within mobile devices and household appliances—it allows our vacuum robot to navigate the living room and enables us to view augmented reality content on our smartphones. By examining simultaneous localization and mapping–based devices and contrasting them against more traditional forms of cartographic practices, we argue that simultaneous localization and mapping technology not only opens up interior spaces for geographic examination but also calls into question the categorical difference between inside and outside itself. As with simultaneous localization and mapping, the mathematical construction of the surrounding space happens in the moment of its detection, simultaneous localization and mapping exhibits a moment of radical situativeness that is freed from the constraints of a stabilized, external database. We propose that this moment of situativeness, which is also inscribed into the resulting highly mobile and fluid visualizations, is the defining feature of a new kind of geomedia that simultaneously establish a vertical and a horizontal geography.

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