Indoor navigation systems incorporating augmented reality allow users to locate places within buildings and acquire more knowledge about their environment. However, although diverse works have been introduced with varied technologies, infrastructure, and functionalities, a standardization of the procedures for elaborating these systems has not been reached. Moreover, while systems usually handle contextual information of places in proprietary formats, a platform-independent model is desirable, which would encourage its access, updating, and management. This paper proposes a methodology for developing indoor navigation systems based on the integration of Augmented Reality and Semantic Web technologies to present navigation instructions and contextual information about the environment. It comprises four modules to define a spatial model, data management (supported by an ontology), positioning and navigation, and content visualization. A mobile application system was developed for testing the proposal in academic environments, modeling the structure, routes, and places of two buildings from independent institutions. The experiments cover distinct navigation tasks by participants in both scenarios, recording data such as navigation time, position tracking, system functionality, feedback (answering a survey), and a navigation comparison when the system is not used. The results demonstrate the system's feasibility, where the participants show a positive interest in its functionalities.
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http://dx.doi.org/10.3390/s21165435 | DOI Listing |
J Imaging
January 2025
Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA.
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View Article and Find Full Text PDFNat Commun
January 2025
Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Aerial manipulators can manipulate objects while flying, allowing them to perform tasks in dangerous or inaccessible areas. Advanced aerial manipulation systems are often based on rigid-link mechanisms, but the balance between dexterity and payload capacity limits their broader application. Combining unmanned aerial vehicles with continuum manipulators emerges as a solution to this trade-off, but these systems face challenges with large actuation systems and unstable control.
View Article and Find Full Text PDFSensors (Basel)
December 2024
SOTI Aerospace, SOTI Inc., Mississauga, ON L5N 8L9, Canada.
Indoor navigation is becoming increasingly essential for multiple applications. It is complex and challenging due to dynamic scenes, limited space, and, more importantly, the unavailability of global navigation satellite system (GNSS) signals. Recently, new sensors have emerged, namely event cameras, which show great potential for indoor navigation due to their high dynamic range and low latency.
View Article and Find Full Text PDFPLoS One
January 2025
Changchun University of Science and Technology, School of Optoelectronic Engineering, Changchun, Jilin, China.
Accurate localization is a critical technology for the application of intelligent robots and automation systems in complex indoor environments. Traditional visual SLAM (Simultaneous Localization and Mapping) techniques often face challenges with localization accuracy in high similarity scenes. To address this issue, this paper proposes an improved visual SLAM loop closure detection algorithm that integrates deep learning techniques.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Business and Commerce, Kansai University, Osaka, 5648680, Japan.
In field of location prediction, trajectory recognition is one of the most widely research issues. Since trajectory includes various information such as position, time, and speed, many scientific methods are applied to extracting meaningful features, and discovering valuable knowledges. This paper pays more attention on case study of in-store trajectory, and proposes a series of recurrent neural network (RNN) for location prediction based on trajectory.
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