• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.108-118
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• 2017

This paper presents experimental results of realtime sonar-based SLAM (simultaneous localization and mapping) using probability-based landmark-recognition. The sonar-based SLAM is used for navigation of underwater robot. Inertial sensor as IMU (Inertial Measurement Unit) and DVL (Doppler Velocity Log) and external information from sonar image processing are fused by Extended Kalman Filter (EKF) technique to get the navigation information. The vehicle location is estimated by inertial sensor data, and it is corrected by sonar data which provides relative position between the vehicle and the landmark on the bottom of the basin. For the verification of the proposed method, the experiments were performed in a basin environment using an underwater robot, yShark.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.6
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• pp.438-445
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• 2019

In this paper, we present a new approach to extract the g-sensitivity scale-factor error for a MEMS gyroscope. MEMS gyroscopes, based on the use of both angular momentum and the Coriolis effect, have a g-sensitivity error due to mass unbalance. Generally, the g-sensitivity error is not considered in general use of gyroscopes, but it deserves our attention if we are to develop for tactical class performance and reliability. The g-sensitivity error during vehicle flight increases navigation error; so it must be analyzed and compensated for the use of MEMS IMU for high dynamics vehicle systems. Therefore, we analyzed how to extract the g-sensitivity scale-factor error from the inertial sensor error model. Furthermore we propose a new method to extract the g-sensitivity error using flight motion simulator. We verified our proposed method with experimental results.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.109-117
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• 2010

With the advent of new technologies such as HSDPA, WiBro(Wireless Broadband) and personal devices, we can access various contents and services anytime and anywhere. A location based service(LBS) is essential for providing personalized services with individual location information in ubiquitous computing environment. In this paper, we propose mapping algorithm for error compensation of indoor localization system. Also we explain filter and indoor localization system. we have developed mapping algorithms composed of a map recognition method and a position compensation method. The map recognition method achieves physical space recognition and map element relation extraction. We improved the accuracy of position searching. In addition, we reduced position errors using a dynamic scale factor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.548-549
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• 2015

무인 잠수정은 자율 무인잠수정(이하 'AUV' 또는 '자율무인잠수정'을 혼용)과 원격조정잠수정(이하 'ROV'로 지칭)으로 분류를 할 수 있다. ROV는 테더 게이블로 인한 작업 범위의 한계와 운동성능 효율이 떨어지는 단점을 지니고 있어, 테더 케이블이 필요 없는 AUV에 대한 필요성이 증대되고 있다. 추측 항법 시스템인 관성 항법 시스템(inertial navigation system, 이하 'INS'로 지칭)은 외부 도움없이 관성측정 장치(inertial measurement unit, 이하 'IMU'로 지칭)를 활용하여 구성된 시스템을 말한다. IMU는 자이로 스코프(gyroscope), 가속도계(accelerometer), 지자기(magnetic)센서로 구성된 측정 장치로 3개의 센서를 사용하여 상호 보정을 통한 기동 체의 위치, 속도 및 자세 정보를 제공한다. 복합항법시스템은 추측항법시스템이 가지는 누적오차와 측위 항법시스템이 가지는 외부환경에 대한 단점을 상호 보완하는 방법으로 연구가 진행 중이다. 하지만 심해서 또는 해양의 특성에 따라 측위 시스템이 사용되지 못하기 때문에 추측 항법시스템의 다양한 관성 센서를 활용한 상로 보완과 신호처리 방법을 통한 연구 개발이 진행 중이다. 다양한 센서 정보를 통합하는 목적으로 칼만 필터와 같은 최적 필터기법이 보편적으로 사용되고 있다. 칼만 필터는 확률 선형 시스템에 대하여 공정잡음 및 측정 잡음이 가우시안 확률 분포를 따를 때 최적의 추정자가 된다. 또한 가우시안 조건을 만족하지 않는 경우에도 선형 추정자 중에 추정 오차의 분산이 가장 작은 추정자이다. 칼만 필터가 최상의 성능을 발휘 하려면 공정잡음과 측정 잡음의 실제 값을 정확히 알아내는 것이 중요하다. 잡음 수준에 대한 정보가 부정확 할 경우 칼만 필터는 발산 할 수 있기 때문에 시스템에서 잡음 수준의 공산은 칼만 필터의 최적 이득을 결정하는 중요한 요소로 추정치에 큰 영향을 준다. 따라서 칼만 필터를 추측항법시스템에 적용 시킬 경우 실제 모텔의 잡음 공분산을 정확히 추정할 수 있는 기법이 요구된다. 추측항법시스템은 다양한 센서를 활용하기 때문에 움직이는 기동 표적에 적용시 잡음공분상이 변하기 때문에 항법시스템이 저하 될 수 있다. 본 연구에서는 다양한 센서를 융합하여 해양 생체 로봇의 정밀 자세 제어가 가능한 시스템을 제안하고자 한다.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.365-372
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• 2022

Compared to sensors mainly used in human activity recognition (HAR) systems, inertial measurement unit (IMU) sensors are small and light, so can achieve lightweight system at low cost. Therefore, in this paper, we propose a binary neural network (BNN) based gait pattern analysis system using IMU sensor, and present the design and implementation results of an FPGA-based accelerator for computational acceleration. Six signals for gait are measured through IMU sensor, and a spectrogram is extracted using a short-time Fourier transform. In order to have a lightweight system with high accuracy, a BNN-based structure was used for gait pattern classification. It is designed as a hardware accelerator structure using FPGA for computation acceleration of binary neural network. The proposed gait pattern analysis system was implemented using 24,158 logics, 14,669 registers, and 13.687 KB of block memory, and it was confirmed that the operation was completed within 1.5 ms at the maximum operating frequency of 62.35 MHz and real-time operation was possible.

• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.19-26
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• 2004

This paper deals with the automatic flight control system for an unmanned target drone which is operated by an army as an anti-air gun shooting training. By automation of unmanned target drone that is manually operated by external pilot, pilot can reduce workload and an army can reduce the budget. Most UAVs which are developed until today use high-cost sensors as AHRS and IMU to measure the attitude, but those are contradictory for the reduction of budget. This paper says the development of low-cost automatic flight control system which makes possible of automatic flight with low-cost sensors. We have developed the integrated automatic flight control system by integrating electricity module, switching module, monitoring module and RC receiver as an one module. We also prove the performance of automatic flight control system by flight test.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.3
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• pp.253-261
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• 2016

A variety of methods for detecting the location of an underground water pipeline are being used across the world; the current main methods used in South Korea, however, have the problems of low precision and efficiency and the limitations in actual application. On this, this study developed locator capable of detecting the location of a water pipe by the use of an IMU sensor, and technology for using the extended karman filter to correct error in location detection and to plot the location on the coordinate system. This study carried out a tract test and a road test as basic experiments to measure the performance of the developed technology and equipment. As a result of the straight line, circular and ellipse track tests, the 1750 IMU sensor showed the average error of 0.08-0.11%; and thus it was found that the developed locator can detect a location precisely. As a result of the 859.6-m road test, it was found that the error was 0.31 m in case the moving rate of the sensor was 0.3-0.6 m/s; and thus it was judged that the equipment developed by this study can be applied to long-distance water pipes of over 1 km sufficiently. It is planned to evaluate its field applicability in the future through an actual pipe network pilot test, and it is expected that locator capable of detecting the location of a water pipe more precisely will be developed through research for the enhancement of accuracy in the algorithm of location detection.

• Spatial Information Research
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• v.11 no.3
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• pp.291-299
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• 2003

The Mobile Mapping System collects geographic information through mounted sensors such as a pair of CCD camera, CPS, IMU(Inertial Measurement Unit) and Odometer at regular distance or time interval. The advantage of such system is to easy identification of positions and geographic informations of mobile objects in real time. Among many wireless communication ways for real-time positions and geographic information data from the mobile mapping system to the user such as PDA, wireless modem, cellophane, and web, the web is considered to be more stabile, effect and economic than any other methods. In this paper, a study on the web-based real-time mobile mapping platform to identify the user position is presented using the real-time NovAtel BDS.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.363-374
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• 2020

In the past, various research on the effects of waves generated by ships has been investigated. The most noticeable effect of the waves generated by a passing ship is the increase of the hydrodynamic forces and the unwanted large motion of the moored ship and high mooring forces that occur. Thus, it is crucial to investigate the effect of the waves generated by the passing ship near port on the motion of the moored ship and the tension of the mooring lines. A model test was performed with virtual ship-generated waves in a square tank at CWNU (Changwon National University). The IMU (Inertial Measurement Unit) and Optical-based system were used to measure the 6DOF (Six Degrees of Freedom) motion of the moored floater. Additionally the tension of mooring lines were measured by the tension gauges. The effects of the wave direction and wave height generated by the virtual ship-generated waves on the motion of the moored floater were analyzed.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.43-50
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• 2014

This paper introduces a robot platform which can do weeding while traveling between rice seedlings stably against irregular land surface of a paddy field. Also, an autonomous navigation technique that can track on stable state without any damage of the seedlings in the working area is proposed. Detection of the rice seedlings and avoidance knocking down by the robot platform is achieved by the sensor fusion of a laser range finder (LRF) and an inertial measurement unit (IMU). These sensors are also used to control navigating direction of the robot to keep going along the column of rice seedling consistently. Deviation of the robot direction from the rice column that is sensed by the LRF is fed back to a proportional and derivative controller to obtain stable adjustment of navigating direction and get proper returning speed of the robot to the rice column.