• International Journal of Internet, Broadcasting and Communication
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• 제8권1호
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• pp.27-32
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• 2016

The global positioning system (GPS)-enabled mobile phones provide location-based applications such as car and pedestrian navigation services. The pedestrian navigation services provide safe and comfortable route and path guidance for pedestrians and handicapped or elderly people. One of the essential components for a navigation system is a spatial database used to perform navigation and routing functions. In this paper, we develop modeling and categorization of pedestrian path components for smart tour guide services using the mobile pedestrian navigation application. We create pedestrian networks using 2D base map and sky view map in urban area. We also construct pedestrian networks and attributes of node, link, and POI using on-site GPS data and photos for smart pedestrian tour guide in the major walking tourist spots in Jeju.

• 전기학회논문지
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• 제59권11호
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• pp.2048-2057
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• 2010

Is this paper, a pedestrian inertial navigation system with vision is proposed. The navigation system using inertial sensors has problems that it is difficult to determine the initial position and the position error increases over time. To solve these problems, a vision system in addition to an inertial navigation system is used, where a camera is attached to a pedestrian. Landmarks are installed to known positions so that the position and orientation of a camera can be computed once a camera views the landmark. Using this position information, estimation errors in the inertial navigation system is compensated.

• 대한공간정보학회지
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• 제19권3호
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• pp.67-74
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• 2011

최근 들어 스마트폰 등 모바일 단말기의 활용이 증대되면서 이동 중인 보행자에게 길안내 서비스를 제공하는 보행자 내비게이션 서비스의 필요성이 증가하고 있다. 이러한 내비게이션 서비스에서 도로 네트워크는 경로와 안내 정보를 생성하는데 있어 가장 핵심적인 요소이다. 하지만, 차량을 위한 도로 네트워크에 비하여 보행 네트워크는 더욱 상세하고 방대한 공간에 대한 모델링 기법이 요구된다. 따라서 기존에 현지 조사와 수동 편집 과정을 통하여 구축하는 방법보다 효율적인 방안이 요구된다. 따라서 본 연구에서는 기 구축되어 있는 차량용 내비게이션 데이터를 기반으로 보행자에게 적합한 보행 네트워크 생성 기법을 제안하였다. 보행 네트워크는 실제 보행자의 이동과 유사한 경로를 생성하기 위하여 보행 공간을 그 특성에 따라 보행 링크(인도, 이면도로, 보행 시설물)와 오픈 스페이스 링크로 구분하고 서로 다른 방법을 적용하여 구축하였다. 이와 같은 기법은 보행 네트워크 생성에 관한 표준 및 방법론이 존재하지 않는 현 시점에서 하나의 효율적인 대안으로 활용될 수 있을 것으로 판단된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1001-1006
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• 2003

This paper presents the pedestrian navigation algorithm and the error compensation filter. The pedestrian navigation system (PNS) consists of the MEMS inertial sensors, the fluxgate, and the small-size GPS receiver. PNS calculates the navigational information using the signal patterns of the accelerometers. And the navigational information is completed by integration of the patterns, the fluxgate, and the GPS information. In general, PNS can provide the better solution than the low-cost inertial navigation system.

• 제어로봇시스템학회논문지
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• 제14권11호
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• pp.1189-1195
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• 2008

We introduce a MEMS-based pedestrian dead reckoning (PDR) system. A walking navigation algorithm for pedestrians is presented and map-matching algorithm for the navigation system based on dead reckoning (DR) is proposed. The PDR is equipped on the human body and provides the position information of pedestrians. And this is able to be used in ubiquitous sensor network (USN), U-hearth monitoring system, virtual reality (VR) and etc. The PDR detects a step using a novel technique and simultaneously estimates step length. Also an azimuth of the pedestrian is calculated using a fluxgate which is the one of magnetometers. Map-matching algorithm can be formulated to integrate the positioning data with the digital road network data. Map-matching algorithm not only enables the physical location to be identified from navigation system but also improves the positioning accuracy. However most of map-matching algorithms which are developed previously are for the car navigation system (CNS). Therefore they are not appropriate to implement to pedestrian navigation system based on DR system. In this paper, we propose walking navigation system and map-matching algorithm for PDR.

• ETRI Journal
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• 제45권5호
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.

• Journal of Positioning, Navigation, and Timing
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• 제10권3호
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• pp.189-196
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• 2021

In this paper, we propose techniques to correct the altitude error and heading error of 3D Pedestrian Inertial Navigation (PIN). When a PIN is used to estimate the location of a pedestrian only with an Inetrial Measurement Unit (IMU) without infrastructure, there is a problem in that the location error gradually increases due to the limitation of the observability of the filter. To solve this problem without additional sensors, we propose two techniques in this paper. First, stair walking is recognized in consideration of the altitude difference that may occur during one step. If it is recognized as stair walking, only Zero-velocity UPdaTe (ZUPT) is performed, and if it is recognized as level walking, ZUPT + Altitude Damping (AD) is performed together to correct the altitude error. Second, the straight-line movement direction is calculated through the difference of the estimated position, and the heading error is corrected by matching this information with the link information of the digital map. By applying these techniques, it is verified through real tests that accurate three-dimensional location information of pedestrians can be estimated without infrastructure.

• Journal of Positioning, Navigation, and Timing
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• 제12권4호
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• pp.399-408
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• 2023

In this paper, we propose a solution that enables continuous indoor/outdoor positioning of smartphone users through the integration of Pedestrian Dead Reckoning (PDR) and GPS/WiFi signals. Considering that accurate step detection affects the accuracy of PDR, we propose a Deep Neural Network (DNN)-based technology to distinguish between walking and non-walking signals such as walking in place. Furthermore, in order to integrate PDR with GPS and WiFi signals, a technique is used to select a proper measurement by distinguishing between indoor/outdoor environments based on GPS Dilution of Precision (DOP) information. In addition, we propose a technology to adaptively change the measurement error covariance matrix by detecting measurement outliers that mainly occur in the indoor/outdoor transition section through a residual-based χ² test. It is verified through experiments on a testbed that these technologies significantly improve the performance of PDR and PDR/GPS/WiFi fingerprinting-based integrated pedestrian navigation.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1309-1323
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• 2020

Crowd evacuation simulation is an important research issue for designing reasonable building layouts and planning more effective evacuation routes. The social force model (SFM) is an important pedestrian movement model, and is widely used in crowd evacuation simulations. The model can effectively simulate crowd evacuation behaviors in a simple scene, but for a multi-obstacle scene, the model could result in some undesirable problems, such as pedestrian evacuation trajectory oscillation, pedestrian stagnation and poor evacuation routing. This paper analyzes the causes of these problems and proposes an improved SFM for complex multi-obstacle scenes. The new model adds navigation points and walking shortest route principles to the SFM. Based on the proposed model, a crowd evacuation simulation system is developed, and the crowd evacuation simulation was carried out in various scenes, including some with simple obstacles, as well as those with multi-obstacles. Experiments show that the pedestrians in the proposed model can effectively bypass obstacles and plan reasonable evacuation routes.

• Journal of Positioning, Navigation, and Timing
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• 제11권1호
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• pp.35-44
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• 2022

In this paper, a dual foot (DF)-PDR system is proposed for the fusion of integration (IA)-based PDR systems independently applied on both shoes. The horizontal positions of the two shoes estimated from each PDR system are fused based on a particle filter. The proposed method bounds the position error even if the walking time increases without an additional sensor. The distribution of particles is a non-Gaussian distribution to express the lateral error due to systematic drift. Assuming that the shoe position is the pedestrian position, the multi-modal position distribution can be fused into one using the Gaussian sum. The fused pedestrian position is used as a measurement of each particle filter so that the position error is corrected. As a result, experimental results show that position of pedestrians can be effectively estimated by using only the inertial sensors attached to both shoes.