• 제목/요약/키워드: indoor localization and tracking

검색결과 36건 처리시간 0.024초

ARVisualizer : A Markerless Augmented Reality Approach for Indoor Building Information Visualization System

  • Kim, Albert Hee-Kwan;Cho, Hyeon-Dal
    • Spatial Information Research
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    • 제16권4호
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    • pp.455-465
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    • 2008
  • 증강현실은 지리정보의 가시화 특히 현장에서의 직접적인 가시화에 있어 매우 높은 잠재력이 있다. 하지만 현재까지의 대부분의 이동형 증강현실 시스템은 사용자의 정확한 위치를 파악하기 위해 GPS 또는 범용적으로 쓰이는 마커를 현장에 붙이는 등의 방식을 사용되었다. 물론 최근의 연구에서 마커없는 환경을 지향하고 있으나 대부분 연구실 또는 제어 환경으로 사용이 제한되어 있다. 특히 실내의 경우 GPS를 사용할 수 없기 때문에 새로운 위치파악기술이 더욱 절실하다. 최근 활발히 활용되고 있는 무선(RF)기반의 실내 위치확인 및 내비게이션 기술 역시 대량의 센서와 인식기를 설치한다는 점에서 그 실용성이 의문이다. 본 연구에서는 단일카메라기반의 SLAM 알고리듬을 이용하여 특수한 하드웨어 없이 카메라만으로 실내 위치 확인 및 내비게이션이 가능한 알고리듬을 제시하였으며, 동시에 확인된 위치에서 증강현실을 통한 정보의 가시화가 가능하도록 구현 하였다. 향후 본 연구가 목표하고 있는 실내외 seamless 연동형 u-GIS 시스템의 기본 기능으로 활용 될 것이다.

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실내 정보 가시화에 의한 u-GIS 시스템을 위한 Markerless 증강현실 방법 (A Markerless Augmented Reality Approach for Indoor Information Visualization System)

  • 김희관;조현달
    • 한국공간정보시스템학회 논문지
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    • 제11권1호
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    • pp.195-199
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    • 2009
  • 증강현실 기술은 실제 환경에 컴퓨터로부터 생성된 가상 데이터를 실시간으로 덧씌우는 기술을 말하며, 이는 지리정보의 가시화 같은 작업에 매우 큰 잠재력을 갖고 있다. 하지만 지금까지 연구된 이동형 증강현실 시스템은 사용자의 위치를 파악하기 위해 GPS(Global Positioning System)를 사용하거나 마커를 현장에 붙이는 방식을 사용하였다. 최근 연구들은 마커를 사용하지 않는 방법을 지향하고 있으나 많은 제약을 갖고 있다. 특히 실내의 경우는 GPS정보를 사용할 수 없기 때문에 실내 위치파악을 위해서는 좀 더 복잡한 문제들을 해결할 수 있는 새로운 기술이 필요하다. 최근 무선(RF, Radio Frequency)기반의 실내 위치 추정 연구가 활발히 수행되고 있지만, 이 또한 다량의 센서와 인식기를 설치해야한다는 제약이 존재한다. 본 연구에서는 한 대의 카메라를 사용하는 SLAM(Simultaneous Localization and Mapping) 알고리듬을 이용한 위치 추정기법을 제시하였으며, 추정된 위치를 이용하여 증강현실을 통한 정보 가시화 프로그램을 개발하였으며 이를. 향후 실내외 seamless 연동이 가능한 모바일 u-GIS (Ubiquitous Geospatial Information System) 시스템에 적용할 것이다.

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SDS-TWR based Location Compensation Mechanism for Localization System in Wireless Sensor Network

  • Lee, Dong-Myung
    • 공학교육연구
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    • 제13권5호
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    • pp.76-80
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    • 2010
  • In this paper, the Location Compensation Mechanism using equivalent distance rate ($LCM_{edr}$) for localization system based on SDS-TWR (Symmetric Double-Sided Two-Way Ranging) in wireless sensor network is proposed. The performance of the mechanism is experimented in terms of two types of the localization tracking scenarios of indoor and outdoor environments in university campus. From the experimentations, the compensation ratio in the $LCM_{edr}$ is better than that in SDS-TWR about 90% in indoor/outdoor environments in scenario 1 but also is better than that of SDS-TWR about 91.7% in indoor environment and about 100% in outdoor environment in scenario 2 respectively.

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Development of a Dynamic Collision Avoidance Algorithm for Indoor Tracking System Based on Active RFID

  • Han, Se-Kyung;Choi, Yeon-Suk;Iwai, Masayuki;Sezaki, Kaoru
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제4권5호
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    • pp.736-752
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    • 2010
  • We propose a novel collision-avoidance algorithm for the active type RFID regarding an indoor tracking system. Several well-known collision avoidance algorithms are analyzed considering the adequacy for the indoor tracking system. We prove the superiority of the slotted ALOHA in comparison with CSMA for short and fixed length packets like an ID message in RFID. Observed results show that they are not applicable for active type RFID in terms of energy efficiency. Putting these all together, we propose a dedicated collision avoidance algorithm considering the unique features of the indoor tracking system. The proposed method includes a scheduled tag access period (STAP) as well as a random tag access period (RTAP) to address both of the static and dynamic characteristics of the system. The system parameters are determined through a quantitative analysis of the throughput and energy efficiency. Especially, some mathematical techniques have been deployed to obtain the optimal slot count for RTAP. Finally, simulation results are provided to illustrate the performance of the proposed method with variations of the parameters.

실내 이동 로봇을 위한 자연 표식과 인공 표식을 혼합한 위치 추정 기법 개발 (Development of Localization using Artificial and Natural Landmark for Indoor Mobile Robots)

  • 안준우;신세호;박재흥
    • 로봇학회논문지
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    • 제11권4호
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    • pp.205-216
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    • 2016
  • The localization of the robot is one of the most important factors of navigating mobile robots. The use of featured information of landmarks is one approach to estimate the location of the robot. This approach can be classified into two categories: the natural-landmark-based and artificial-landmark-based approach. Natural landmarks are suitable for any environment, but they may not be sufficient for localization in the less featured or dynamic environment. On the other hand, artificial landmarks may generate shaded areas due to space constraints. In order to improve these disadvantages, this paper presents a novel development of the localization system by using artificial and natural-landmarks-based approach on a topological map. The proposed localization system can recognize far or near landmarks without any distortion by using landmark tracking system based on top-view image transform. The camera is rotated by distance of landmark. The experiment shows a result of performing position recognition without shading section by applying the proposed system with a small number of artificial landmarks in the mobile robot.

A Location Tracking System using BLE Beacon Exploiting a Double-Gaussian Filter

  • Lee, Jae Gu;Kim, Jin;Lee, Seon Woo;Ko, Young Woong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권2호
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    • pp.1162-1179
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    • 2017
  • In this paper, we propose indoor location tracking method using RSSI(Received Signal Strength Indicator) value received from BLE(Bluetooth Low Energy) beacon. Due to the influence of various external environmental factors, it is very difficult to improve the accuracy in indoor location tracking. In order to solve this problem, we propose a novel method of reducing the noise generated in the external environment by using a double Gaussian filter. In addition, the value of the RSSI signal generated in the BLE beacon is different for each device. In this study, we propose a method to allocate additional weights in order to compensate the intensity of signal generated in each device. This makes it possible to improve the accuracy of indoor location tracking using beacons. The experiment results show that the proposed method effectively decrease the RSSI deviation and increase location accuracy. In order to verify the usefulness of this study, we compared the Kalman filter algorithm which is widely used in signal processing. We further performed additional experiments for application area for indoor location service and find that the proposed scheme is useful for BLE-based indoor location service.

Application of Kalman Filter to Cricket based Indoor localization system

  • Kim, Sung-Ho;Zhang, Chong-Yi
    • 한국지능시스템학회논문지
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    • 제18권4호
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    • pp.537-542
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    • 2008
  • Cricket is an excellent indoor location system and it can successfully solve many critical problems such as user privacy, decentralized administration. But in some practical applications, Cricket sometimes didn't provide location with enough accuracy, and was unable to determine when it was giving inaccurate information. For getting high-accuracy tracking performance from location data contaminated with noise, some types of filters are required. Kalman Filter is an efficient recursive filter that estimates the state of a dynamic system from a series of incomplete and noisy measurement. The filter is very powerful in the field of autonomous and assisted navigation. In this paper, we carry out comparative studies to validate the performance of the application of Kalman Filter to Cricket based localization system.

시뮬레이션을 이용한 누적 RSSI 신호 기반의 항법 기술 성능 분석 (Analysis of Localization Technology Performance Based on Accumulated RSSI Signal Using Simulation)

  • 신범주;이택진
    • Journal of Positioning, Navigation, and Timing
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    • 제13권3호
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    • pp.331-339
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    • 2024
  • Reliable and precise indoor localization is crucial for personal navigation, emergency rescue, and monitoring workers indoors. To use this technology in different applications, it is important to make it less dependent on infrastructure and to keep the error as small as possible. Fingerprinting stands out as a popular choice for indoor positioning because it leverages existing infrastructure and works with just a smartphone. However, its accuracy heavily relies on the quality of that infrastructure. For instance, having too few access points or beacons can greatly reduce its effectiveness. To reduce dependence on RF infrastructure, we have developed surface correlation (SC) using accumulated Received Signal Strength Indicator (RSSI) signals This approach constructs a user mask for radio map comparisons using an accumulated RSSI vector and the trajectory of the user, which is estimated through PDR. The location with the highest correlation is considered as the user's position after comparison. Through a simulation, the performance of short RSSI vector-based technology and SC is analyzed, and future directions for the development of SC are discussed.

연속 자유 공간에서 가우시안 보간법을 이용한 보행자 위치 추적 (Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces)

  • 김인철;최은미;오휘경
    • 정보처리학회논문지B
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    • 제19B권3호
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    • pp.177-182
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    • 2012
  • 본 논문에서는 대규모 실내 환경에서 WiFi 모듈이 내장된 스마트폰 사용자의 위치를 추적하기 위한 효과적인 이동 모델과 관측 모델을 제시한다. 제안하는 세 가지 부속 이동 모델들은 보행자의 움직임에 대한 더 정확한 예상 확률 분포를 제공한다. 또, 가우시안 보간법 기반의 관측 모델은 훈련 데이터 의 수집이 이루어지지 않은 지역들에 대해서도 관측 우도 계산을 가능하게 한다. 파티클 필터 프레임워크 속에 이와 같은 이동 모델과 관측 모델을 결합함으로써, 본 연구의 위치 추적 알고리즘은 대규모 실내 환경들에서도 스마트폰 사용자의 위치를 정확하게 추적할 수 있다. 한 복층 건물에서 안드로이드 스마트폰으로 수행한 실험을 통해, 본 연구에서 제안한 WiFi 위치 추적 알고리즘의 성능을 확인할 수 있었다.

무선 센서네트워크에서의 통계적 방법에 의한 실내 RSSI 측정 (Indoor RSSI Characterization using Statistical Methods in Wireless Sensor Network)

  • 푸촨친;정완영
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2007년도 추계종합학술대회
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    • pp.457-461
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    • 2007
  • In many applications, received signal strength indicator is used for location tracking and sensor nodes localization. For location finding, the distances between sensor nodes can be estimated by converting received signal's power into distance using path loss prediction model. Many researches have done the analysis of power-distance relationship for radio channel characterization. In indoor environment, the general conclusion is the non-linear variation of RSSI values as distance varied linearly. This has been one of the difficulties for indoor localization. This paper presents works on indoor RSSI characterization based on statistical methods to find the overall trend of RSSI variation at different places and times within the same room From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. This two factors are directly indicated by the two main parameters of path loss prediction model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. Using this relationship, the characterization for location estimation can be more efficient and accurate.

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