• Title/Summary/Keyword: infrastructure-based localization

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Infrastructure-based Localization System using Underwater Wireless Sensor Network (구조화된 공간에서의 수중 무선 센서 네트워크를 이용한 위치 추정 시스템)

  • Park, Dae-Gil;Kwak, Kyung-Min;Chung, Wan-Kyun;Kim, Jin-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.8
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    • pp.699-705
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    • 2012
  • In this paper, an infrastructure-based localization method using underwater wireless sensor network (UWSN) is addressed. A localization using the UWSN is necessary to widen the usage of underwater applications, however it is very difficult to establish the UWSN due to the restrictions of water. In this paper, to extend the usage of UWSN at the infrastructure, we propose a sophisticated UWSN localization method using the Received Signal Strength Indicator (RSSI) of the electromagnetic waves. During the electromagnetic waves propagating in underwater, there arises a lot of attenuation according to the distance, while the attenuation shows uniformity according to the distance. Using this characteristics, the localization system in underwater infrastructure is proposed and the experimental results show the effectiveness.

A Range-Based Localization Algorithm for Wireless Sensor Networks

  • Zhang Yuan;Wu Wenwu;Chen Yuehui
    • Journal of Communications and Networks
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    • v.7 no.4
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    • pp.429-437
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    • 2005
  • Sensor localization has become an essential requirement for realistic applications over wireless sensor networks (WSN). In this paper we propose an ad hoc localization algorithm that is infrastructure-free, anchor-free, and computationally efficient with reduced communication. A novel combination of distance and direction estimation technique is introduced to detect and estimate ranges between neighbors. Using this information we construct unidirectional coordinate systems to avoid the reflection ambiguity. We then compute node positions using a transformation matrix [T], which reduces the computational complexity of the localization algorithm while computing positions relative to the fixed coordinate system. Simulation results have shown that at a node degree of 9 we get $90\%$ localization with $20\%$ average localization error without using any error refining schemes.

Pedestrian Navigation System in Mountainous non-GPS Environments

  • Lee, Sungnam
    • Journal of information and communication convergence engineering
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    • v.19 no.3
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    • pp.188-197
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    • 2021
  • In military operations, an accurate localization system is required to navigate soldiers to their destinations, even in non-GPS environments. The global positioning system is a commonly used localization method, but it is difficult to maintain the robustness of GPS-based localization against jamming of signals. In addition, GPS-based localization cannot provide important terrain information such as obstacles. With the widespread use of embedded sensors, sensor-based pedestrian tracking schemes have become an attractive option. However, because of noisy sensor readings, pedestrian tracking systems using motion sensors have a major drawback in that errors in the estimated displacement accumulate over time. We present a group-based standalone system that creates terrain maps automatically while also locating soldiers in mountainous terrain. The system estimates landmarks using inertial sensors and utilizes split group information to improve the robustness of map construction. The evaluation shows that our system successfully corrected and combined the drift error of the system localization without infrastructure.

Sensor Information Filter for Enhancing the Indoor Pedestrian Localization Accuracy (보행자의 실내 위치 추정 정확도 향상을 위한 다양한 센서 정보 필터)

  • Kim, Jooyoung;Lee, Sooyong
    • The Journal of Korea Robotics Society
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    • v.7 no.4
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    • pp.276-283
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    • 2012
  • Due to the low localization accuracy and the requirement of special infrastructure, current LBS(Localization Based Service) is limited to show P.O.I.(Point of Interest) nearby. Improvement of IMU(Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more information of movement. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization.

Estimation of the User's Location/Posture for Mobile Augmented Reality (모바일 증강현실 구현을 위한 사용자의 위치/자세 추정)

  • Kim, Jooyoung;Lee, Sooyong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.11
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    • pp.1011-1017
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    • 2012
  • Augmented Reality is being widely used not only for Smartphone users but also in industries such as maintenance, construction area. With smartphone, due to the low localization accuracy and the requirement of special infrastructure, current LBS (Localization Based Service) is limited to show P.O.I. (Point of Interest) nearby. Improvement of IMU (Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more movement information. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization. Additional sensors are used to measure the movements of the upper body and the head and to provide the user's line of sight.

TWR based Cooperative Localization of Multiple Mobile Robots for Search and Rescue Application (재난 구조용 다중 로봇을 위한 GNSS 음영지역에서의 TWR 기반 협업 측위 기술)

  • Lee, Chang-Eun;Sung, Tae-Kyung
    • The Journal of Korea Robotics Society
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    • v.11 no.3
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    • pp.127-132
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    • 2016
  • For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

Automatic Mutual Localization of Swarm Robot Using a Particle Filter

  • Lee, Yang-Weon
    • Journal of information and communication convergence engineering
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    • v.10 no.4
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    • pp.390-395
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    • 2012
  • This paper describes an implementation of automatic mutual localization of swarm robots using a particle filter. Each robot determines the location of the other robots using wireless sensors. The measured data will be used for determination of the movement method of the robot itself. It also affects the other robots' self-arrangement into formations such as circles and lines. We discuss the problem of a circle formation enclosing a target that moves. This method is the solution for enclosing an invader in a circle formation based on mutual localization of the multi-robot without infrastructure. We use trilateration, which does require knowing the value of the coordinates of the reference points. Therefore, specifying the enclosure point based on the number of robots and their relative positions in the coordinate system. A particle filter is used to improve the accuracy of the robot's location. The particle filter is operates better for mutual location of robots than any other estimation algorithms. Through the experiments, we show that the proposed scheme is stable and works well in real environments.

A Study of Temporary Positioning Scheme with IoT devices for Disastrous Situations in Indoor Spaces Without Permanent Network Infrastructure (상설 네트워크 인프라가 없는 실내 공간에서 재난시 IoT 기기를 활용한 부착형 실내 위치 추적 기술 연구)

  • Lee, Jeongpyo;Yun, Younguk;Kim, Sangsoo;Kim, Youngok
    • Journal of the Society of Disaster Information
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    • v.14 no.3
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    • pp.315-324
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    • 2018
  • Purpose: This paper propose a temporary indoor positioning scheme with devices of internet of things (IoT) for disastrous situations in places without the infrastructure of networks. Method: The proposed scheme is based on the weighted centroid localization scheme that can estimate the position of a target with simple computation. Results: It also is implemented with the IoT devices at the underground parking lot, where the network is not installed, of general office building. According to the experiment results, the positioning error was around 10m without a priori calibration process at $82.5m{\times}56.4m$ underground space. Conclusion: The proposed scheme can be deployed many places without the infrastructure of networks, such as parking lots, warehouses, factory, etc.

Experimental validation of a multi-level damage localization technique with distributed computation

  • Yan, Guirong;Guo, Weijun;Dyke, Shirley J.;Hackmann, Gregory;Lu, Chenyang
    • Smart Structures and Systems
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    • v.6 no.5_6
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    • pp.561-578
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    • 2010
  • This study proposes a multi-level damage localization strategy to achieve an effective damage detection system for civil infrastructure systems based on wireless sensors. The proposed system is designed for use of distributed computation in a wireless sensor network (WSN). Modal identification is achieved using the frequency-domain decomposition (FDD) method and the peak-picking technique. The ASH (angle-between-string-and-horizon) and AS (axial strain) flexibility-based methods are employed for identifying and localizing damage. Fundamentally, the multi-level damage localization strategy does not activate all of the sensor nodes in the network at once. Instead, relatively few sensors are used to perform coarse-grained damage localization; if damage is detected, only those sensors in the potentially damaged regions are incrementally added to the network to perform finer-grained damage localization. In this way, many nodes are able to remain asleep for part or all of the multi-level interrogations, and thus the total energy cost is reduced considerably. In addition, a novel distributed computing strategy is also proposed to reduce the energy consumed in a sensor node, which distributes modal identification and damage detection tasks across a WSN and only allows small amount of useful intermediate results to be transmitted wirelessly. Computations are first performed on each leaf node independently, and the aggregated information is transmitted to one cluster head in each cluster. A second stage of computations are performed on each cluster head, and the identified operational deflection shapes and natural frequencies are transmitted to the base station of the WSN. The damage indicators are extracted at the base station. The proposed strategy yields a WSN-based SHM system which can effectively and automatically identify and localize damage, and is efficient in energy usage. The proposed strategy is validated using two illustrative numerical simulations and experimental validation is performed using a cantilevered beam.

Real Time Indoor Localization Using Geomagnetic Fingerprinting and Pedestrian Dead Reckoning (지구 자기장 기반 지문인식 및 추측 항법을 결합한 실시간 실내 위치정보 서비스)

  • Jang, HoJun;Choi, Lynn
    • KIISE Transactions on Computing Practices
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    • v.23 no.4
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    • pp.210-216
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    • 2017
  • In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.