• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.33-40
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• 2017

In this paper, we introduce commercial indoor navigation systems being deployed and serviced in many fields of industry focusing on their indoor positioning technologies. Indoor positioning technology is a technology that locates people or targets in the interior of a building. To do that, it utilizes radio waves such as WiFi, and bluetooth, magnetic fields, or other sensory information from smart phones. We present indoor navigation systems categorizing them into their indoor positioning technologies. We define important performance issues for indoor positioning technologies and analyze them according to the performance issues. We believe that this paper provide wise view and necessary information for recent indoor navigation systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4606-4623
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• 2019

Nowadays modern cities develop in a very rapid speed. Buildings become larger than ever and the interior structures of the buildings are even more complex. This drives a high demand for precise and accurate indoor navigation systems. Although the existing commercially available 2D indoor navigation system can help users quickly find the best path to their destination, it does not intuitively guide users to their destination. In contrast, an indoor navigation system combined with augmented reality technology can efficiently guide the user to the destination in real time. Such practical applications still have various problems like position accuracy, position drift, and calculation delay, which causes errors in the navigation route and result in navigation failure. During the navigation process, the large computation load and frequent correction of the displayed paths can be a huge burden for the terminal device. Therefore, the navigation algorithm and navigation logic need to be improved in the practical applications. This paper proposes an improved navigation algorithm and navigation logic to solve the problems, creating a more accurate and effective augmented reality indoor navigation system.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.3
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• pp.145-156
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• 2016

A variety of methods for indoor positioning systems have been underway to ensure the safety of emergency rescuers who are working in dangerous situations such as fire fighters. However, since most systems display locations of rescue workers in two-dimension (2D)-based maps, it is difficult for a commander located in the outside to recognize locations of rescuers inside the building intuitively. An augmented reality (AR)-based indoor positioning monitoring system can display locations of rescuer inside the building that can be seen by commanders to help intuitive recognition of positioning. To monitor AR-based indoor positioning, it is necessary to have an estimation technique of line of sight vector of observers. In the present study, an estimation technique of a line of sight vector using ultra-wide band tranceiver installed inside the indoor to trace locations is presented.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.205-211
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• 2020

In this paper, we propose a modified ORB-SLAM (Oriented FAST and Rotated BRIEF Simultaneous Localization And Mapping) for precise indoor navigation of a mobile robot. The exact posture and position estimation by the ORB-SLAM is not possible all the times for the indoor navigation of a mobile robot when there are not enough features in the environment. To overcome this shortcoming, additional IMU (Inertial Measurement Unit) and encoder sensors were installed and utilized to calibrate the ORB-SLAM. By fusing the global information acquired by the SLAM and the dynamic local location information of the IMU and the encoder sensors, the mobile robot can be obtained the precise navigation information in the indoor environment with few feature points. The superiority of the modified ORB-SLAM was verified to compared with the conventional algorithm by the real experiments of a mobile robot navigation in a corridor environment.

• Spatial Information Research
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• v.21 no.2
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• pp.1-9
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• 2013

Recently many researches have focused on indoor navigation system. An optimal indoor navigation method can help people to find a path in large and complex buildings easily. However, some indoor navigation algorithms only calculate approximate routes based on spatial topology analysis, while others only use indoor road networks. However, both of them use only one of the spatial topology or network information. In this paper, we present a navigation method based on topology analysis and room internal networks for indoor navigation path. FT-Indoornavi (Flexible Topology Analysis Indoornavi) calculate internal routes based on spatial topology and internal path networks to support length-dependent and running-time optimal routing, which adapt to complex indoor environment and can achieve a better performance in comparison of Elastic algorithm and iNav.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.181-194
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• 2017

In recent years, research has been actively conducted on the navigation in an indoor environment where Global Navigation Satellite System signals are unavailable. Among them, a study performed indoor navigation by integrating pseudolite carrier and Inertial Measurement Unit (IMU) sensor. However, in this case, there was no solution for the cycle slip occurring in the carrier. In another study, cycle slip detection and compensation were performed by integrating Global Positioning System (GPS) and IMU in an outdoor environment. However, in an indoor environment, cycle slip occurs more easily and frequently, and thus the occurrence of half cycle slip also increases. Accordingly, cycle slip detection based on 1 cycle unit has limitations. Therefore, in the present study, the aforementioned problems were resolved by performing indoor navigation through the integration of pseudolite and ultra-low-cost IMU embedded in a smartphone and by performing half cycle slip detection and compensation based on this. In addition, it was verified through the actual implementation of real-time navigation.

• ETRI Journal
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• v.40 no.4
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• pp.446-457
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• 2018

Robot navigation allows robot mobility. Therefore, mobility is an area of robotics that has been actively investigated since robots were first developed. In recent years, interest in personal service robots for homes and public facilities has increased. As a result, robot navigation within the home environment, which is an indoor environment, is being actively investigated. However, the problem with conventional navigation algorithms is that they require a large computation time for their building mapping and path planning processes. This problem makes it difficult to cope with an environment that changes in real-time. Therefore, we propose a humanoid robot navigation algorithm consisting of an image processing and optimization algorithm. This algorithm realizes navigation with less computation time than conventional navigation algorithms using map building and path planning processes, and can cope with an environment that changes in real-time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.359-366
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• 2019

Indoor spatial data has great importance as the demand for representing the complex urban environment in the context of providing LBS (Location-based Services) is increasing. IndoorGML (Indoor Geographic Markup Language) has been established as the data standard for spatial data in providing indoor navigation, but its definitions and relationships must be expanded to increase its applications and to successfully delivering information to users. In this study, we propose an approach to integrate IndoorGML with Indoor POI (Points of Interest) data by extending the IndoorGML notion of space and topological relationships. We consider two cases of representing Indoor POI, by 3D geometry and by point primitive representation. Using the concepts of the NRS (node-relation structure) and multi-layered space representation of IndoorGML, we define layers to separate features that represent the spaces and the Indoor POI into separate, but related layers. The proposed methodology was implemented with real datasets to evaluate its effectiveness for performing indoor spatial analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.173-182
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• 2015

A real-time, Indoor navigation systems utilize ultra-wide band (UWB), radio-frequency identification (RFID) and received signal strength (RSS) techniques that encompass WiFi, FM, mobile communications, and other similar technologies. These systems typically require surplus infrastructure for their implementation, which results in significantly increased costs and complexity. Therefore, as a solution to reduce the level of cost and complexity, an inertial measurement unit (IMU) and quick response (QR) codes are utilized in this paper to facilitate navigation with the assistance of a smartphone. The QR code helps to compensate for errors caused by the pedestrian dead reckoning (PDR) algorithm, thereby providing more accurate localization. The proposed algorithm having IMU in conjunction with QR code shows an accuracy of 0.64 m which is higher than existing indoor navigation techniques.