• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.1122-1140
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• 2024

The importance of indoor positioning has grown in numerous application areas such as emergency response, logistics, and industrial automation. In ships, indoor positioning is also needed to provide services to passengers on board. Due to the complex structure and dynamic nature of ship environments, conventional positioning techniques have limitations in providing accurate positions. Compared to other indoor positioning technologies, Bluetooth 5.1-based indoor positioning technology is highly suitable for ship environments. Bluetooth 5.1 attains centimeter-level positioning accuracy by collecting In-phase and Quadrature (IQ) samples from wireless signals. However, distorted IQ samples can lead to significant errors in the final estimated position. Therefore, we propose an indoor positioning method for ships that utilizes a Deep Neural Network (DNN) combined with IQ fingerprint maps to overcome the challenges associated with accurate location detection within the ship. The results indicate that the accuracy of our proposed method can reach up to 97.76%.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.50-55
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• 2023

Due to the unavailability of global positioning system (GPS) indoors, various indoor pedestrian positioning methods have been designed to estimate the position of the user using received signal strength (RSS) measurements from radio beacons, such as wireless fidelity (WiFi) access points and Bluetooth low energy (BLE) beacons. In indoor environments, radio-frequency (RF) signals are unpredictable and change over space and time because of multipath associated with reflection and refraction, shadow fading caused by obstacles, and interference among different devices using the same frequencies. Therefore, the outliers in the positional information obtained from the indoor positioning method based on RSS measurements occur often. For this reason, the performance of the positioning method can be degraded by the characteristics of the RF signal. To resolve this issue, a map-matching (MM) algorithm based on maximum probability (MP) estimation is applied to the indoor positioning method in this study. The MM algorithm locates the aberrant position of the user estimated by the positioning method within the limits of the adjacent pedestrian passages. Empirical experiments show that the positioning method can achieve higher positioning accuracy by leveraging the MM algorithm.

• 한국컴퓨터정보학회논문지
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• 제16권8호
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• pp.147-155
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• 2011

위치기반서비스 시스템의 주요 컴포넌트에는 도면출력, 측위, 데이터베이스 관리 등이 포함된다. 도면출력은 일반적으로 구글 지도를 사용하며 측위는 GPS(Global Positioning System)를 사용한다. 그러나 위치기반서비스를 옥내에서 구현하려면 이러한 일반적인 솔루션을 사용할 수가 없다. 즉, 구글 지도로 건물 내부 도면을 출력할 수도 없고, GPS로 건물 내부의 이동객체의 위치를 측정할 수도 없다. 본 연구는 도면출력 기능, 옥내측위 기능 그리고 데이터베이스에 콘텐츠 업로드 및 출력 기능들을 웹서비스로 구현한 사례를 소개하여, 프로그램 개발자가 누구나 쉽게 호출하여 사용할 수 있게 한다. 구현한 웹서비스들의 효용성을 실험적으로 보이기 위하여 이러한 웹서비스들을 이용하여 박물관 관람객의 위치를 고려한 콘텐츠 출력 시스템 프로토타입을 구현한다.

• 로봇학회논문지
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• 제18권4호
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• pp.487-495
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• 2023

This paper presents a method for autonomous exploration of indoor environments using a 2-dimensional Light Detection And Ranging (LiDAR) scanner. The proposed frontier-based exploration method considers navigability from the current robot position to extracted frontier targets. An approach to constructing the point cloud grid map that accurately reflects the occupancy probability of glass obstacles is proposed, enabling identification of safe frontier grids on the safety grid map calculated from the point cloud grid map. Navigability, indicating whether the robot can successfully navigate to each frontier target, is calculated by applying the skeletonization-informed rapidly exploring random tree algorithm to the safety grid map. While conventional exploration approaches have focused on frontier detection and target position/direction decision, the proposed method discusses a safe navigation approach for the overall exploration process until the completion of mapping. Real-world experiments have been conducted to verify that the proposed method leads the robot to avoid glass obstacles and safely navigate the entire environment, constructing the point cloud map and calculating the navigability with low computing time deviation.

• 한국소음진동공학회논문집
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• 제23권4호
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• pp.295-300
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• 2013

The noise map can be applied to predict the effect of noise and establish the noise reduction measure. But the predicted value in the noise map can vary depending on the input variables. Thus, we surveyed the several prediction models and analyzed the changes corresponding to the variables for obtaining the coherency and accuracy of prediction results. As a result, we know that the Schall03 and CRN model can be applied to predict the railway noise in Korea and the correction value, such as bridges correction, multiple reflection correction, curve correction must be used for reflecting the condition of the prediction site. Also, we know that the prediction guideline is an essential prerequisite in order to obtain the unified and accurate predicted value for railway noise.

• 한국생산제조학회지
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• 제20권2호
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• pp.133-138
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• 2011

RFID system can be used to improve object recognition, map building and localization for robot area. A novel method of indoor navigation system for a mobile robot is proposed using RFID technology. The mobile robot With a RFID reader and antenna is able to find what obstacles are located where in circumstance and can build the map similar to indoor circumstance by combining RFID information and distance data obtained from sensors. Using the map obtained, the mobile robot can avoid obstacles and finally reach the desired goal by $A^*$ algorithm. 3D map which has the advantage of robot navigation and manipulation is able to be built using z dimension of products. The proposed robot navigation system is proved to apply for SLAM and path planning in unknown circumstance through numerous experiments.

• 대한임베디드공학회논문지
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• 제9권6호
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• pp.323-334
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• 2014

In this paper, we proposed indoor positioning system with improved accuracy. The proposed indoor location measurement system is based pedestrian location measurement method that use the embedded sensor of smartphone. So, we do not need wireless external resources, such as GPS or WiFi signals. The conventional methods measure indoor location by generating a movement route of pedestrian by step and direction recognition. In this paper, to correct the direction sensor error, we use the common feature of the normal indoor floor map that the indoor path is lattice-structured. And we quantize moving directions depending on the direction of indoor path. In addition, we propose moving direction measuring method using geomagnetic sensor and gyro sensor to improve the accuracy. Also, the proposed step detection method uses angle and accelerometer sensors. The proposed step detection method is not affected by the posture of the smartphone. Direction errors caused by direction sensor error is corrected due to proposed moving direction measuring method. The proposed location error correction method corrects location error caused by step detection error without the need for external wireless signal resources.

• 전기학회논문지
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• 제68권3호
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• pp.471-479
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• 2019

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.59-61
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• 2022

무선 AP를 이용한 실내 측위 시스템 기법 중 핑거프린트 기법은 측위를 수행하기 전 AP의 Mac 정보와 수신세기를 수집하여 Radio Map을 구축하고 이후 측위 과정에서 수집되는 AP의 정보와 비교하여 위치를 판단하는 기법이다. 단, 기존 Radio Map 구축방법은 실내를 일정한 크기의 Grid Map으로 나누어 측정했을 때 실내 환경에 따라 수많은 AP들의 충돌로 인한 상호간의 신호 간섭이 발생, 신호 패턴에 영향을 주어 신호 세기 탐색 결과가 항상 일정하게 나오지 않는 문제점이 있다. 이에 본 논문에서는 기존의 고정형 Radio Map 구축 방법과 측정 구역 자체를 신호 세기에 따라 능동적으로 분석하여 구성하는 가변적 Radio Map 구축기법에 대하여 비교 설명한다.

• 한국통신학회논문지
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• 제41권8호
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• pp.986-994
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• 2016

본 논문에서는 초음파 센서를 활용한 2D 실내 지도 작성을 위하여 회전형 모듈과 고정형 모듈을 개발하여 각 모듈의 가능성과 한계점을 확인하였으며, 초음파 센서를 활용하여 실내 지도 작성 시에 고려하여야 할 센서 특성 실험과 2D 실내 지도 작성 결과를 기술한다. 최근 실내 공간에서의 simultaneous localization and mapping(SLAM) 기술이 많은 주목을 받으면서 이와 더불어 실내 공간을 인식하여 지도정보로 만들기 위한 기술연구 또한 활발히 진행되고 있고, 이를 위한 기술로써 LiDAR, 초음파, 카메라 등이 많이 사용 되고 있다. 가장 좋은 성능을 지닌 LiDAR 기술의 경우 초음파에 비해 높은 해상력과 넓은 탐지범위를 가지고 있지만 모듈 크기의 한계, 높은 비용, 많은 연산량 그리고 비교적 다양한 매질에 따른 노이즈에 약한 특성이 있다. 이에 따라 본 논문에서는 초음파 센서를 활용하여, 레이저 센서의 취약점을 보완함과 동시에 비교적 적은 연산량을 가지며 최소한의 초음파 센서를 사용한 2D 실내 지도 작성 기법을 제안하며 실험을 통하여 이를 검증하였다.