• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.562-569
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• 2016

This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.249-255
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• 2002

Since the stationary alignment process of the SDINS is not completely observable, some furls of the aided alignment have been applied. The purpose of this paper is to propose a new initial alignment algorithm, which utilizes the attitude output from the AGPS(Attitude Determination GPS) receiver and to demonstrate the feasibility of the proposed algorithm with several experimental results. A Kalman filter is designed for utilizing the attitude output as well as the zero velocity information. Also analyzed is the observability of the SDINS error model. To show the feasibility of the proposed scheme, we implement an alignment system where HG1700AE IMU (Inertial Measurement Unit) from Honeywell and an AGPS receiver designed at Chungnam National University are used. Test trials are done to evaluate the performance of the proposed alignment scheme. The proposed algorithm provides as good initial alignment performance as a high accurate navigation system, MAPS(Modular Azimuth Positioning System) INS.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.5
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• pp.439-446
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• 2019

A real time transporter locating system for shipyard has been implemented through the GNSS and IMU sensor. There are a lot of block movements by transporters at the shipyard, which need to be controlled and monitored for conforming to the shipbuilding process. For the precise and safe transporter motion at the yard, a locating system has been developed by using the GNSS and IMU sensors for the transporter. There are several obstacles of the GPS signals for locating the transporter at the yard, such as, buildings and metal structures. To overcome the weakness of the GPS signal transmission, the IMU data have been properly integrated together. The performance of the proposed real time block locating system has been verified through the real experiments with transporters carrying blocks at a shipyard.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1034-1037
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• 2015

In recent years in the field of robotics, various methods have been developed to create an intimate relationship between people and robots. These methods include speech, vision, and biometrics recognition as well as gesture-based interaction. These recognition technologies are used in various wearable devices, smartphones and other electric devices for convenience. Among these technologies, gesture recognition is the most commonly used and appropriate technology for wearable devices. Gesture recognition can be classified as contact or noncontact gesture recognition. This paper proposes contact gesture recognition with IMU and EMG sensors by using the hidden Markov model (HMM) twice. Several simple behaviors make main gestures through the one-stage HMM. It is equal to the Hidden Markov model process, which is well known for pattern recognition. Additionally, the sequence of the main gestures, which comes from the one-stage HMM, creates some higher-order gestures through the two-stage HMM. In this way, more natural and intelligent gestures can be implemented through simple gestures. This advanced process can play a larger role in gesture recognition-based UX for many wearable and smart devices.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.489-497
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• 2010

This paper presents the design of hardware platform, which is a test bed for the navigation system and hovering type AUV (Autonomous Underwater Vehicle) under the OCP (Open Control Platform). The developed AUV test bed consists of two hulls, four thrusters, and the navigation system which uses a SBC2440II with IMU (Inertial Measurement Unit). And the SMC (Sliding Mode Control) is chosen for the diving and steering control of the AUV. This paper uses ACE/TAO RTEC (Real-Time Event Channel) as a middleware platform in order to control and communicate in the developed AUV test bed. In this paper, two computers are used and each of them is dedicated for the specific purpose, the first computer is used as the SMC module and the middleware platform for the ACE/TAO RTEC and the second computer is used for the sensor controller. We analyze the performance of the AUV test bed under the OCP.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.611-616
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• 2008

When extracting geo-referenced 3D data from cameras mounted on Mobile Mapping Systems, one of important properties for accuracy of extracted data is the alignment of the relative translation(lever-arm) and rotation(bore-sight) between the coordinate systems of Inertial Measurement Unit(IMU)/Ground Positioning System(GPS) and cameras. Since the conventional method calculates absolute camera orientation using ground control points (GCP), the alignment is determined in one Coordinated System (GPS Coordinated System). It basically require GCP. We proposed a mathematical model for the alignment using the initially uncoupled data of cameras and IMU/GPS without GCPs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.425-433
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• 2020

Three-dimensional data has been used for different applications such as robotics, building reconstruction, and so on. 3D data can be generated from an optical camera or a laser scanner. Especially, a wearable multi-sensor system including the above-mentioned sensors is an optimized structure that can overcome the drawbacks of each sensor. After finding the geometric relationships between sensors, georeferencing of the datasets acquired from the moving system, should be carried out. Especially, in an indoor environment, error propagation always causes problem in the georeferencing process. To improve the accuracy of this process, other sources of data were used to combine with LiDAR (Light Detection and Ranging) data, and various registration methods were also tested to find the most suitable way. More specifically, this paper proposed a new process of NDT (Normal Distribution Transform) to register the LiDAR point cloud, with additional information from other sensors. For real experiment, a wearable mapping system was used to acquire datasets in an indoor environment. The results showed that applying the new process of NDT and combining LiDAR data with IMU (Inertial Measurement Unit) information achieved the best result with the RMSE 0.063 m.

• Journal of Sensor Science and Technology
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• v.29 no.6
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• pp.440-446
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• 2020

A well-known difficulty in attitude estimation based on inertial measurement unit (IMU) signals is the occurrence of external acceleration under dynamic motion conditions, as the acceleration significantly degrades the estimation accuracy. Lee et al. (2012) designed a Kalman filter (KF) that could effectively deal with the acceleration issue. Ahmed and Tahir (2017) modified this method by adjusting the acceleration-related covariance matrix because they considered covariance modeling as a pivotal factor in the estimation accuracy. This study investigates the effects of covariance modeling on estimation accuracy in an IMU-based attitude estimation KF. The method proposed by Ahmed and Tahir can be divided into two: one uses the covariance including only diagonal components and the other uses the covariance including both diagonal and off-diagonal components. This paper compares these three methods with respect to the motion condition and the window size, which is required for the methods by Ahmed and Tahir. Experimental results showed that the method proposed by Lee et al. performed the best among the three methods under relatively slow motion conditions, whereas the modified method using the diagonal covariance with a high window size performed the best under relatively fast motion conditions.

• Journal of the Korean Institute of Gas
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• v.6 no.1 s.17
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• pp.52-58
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• 2002

The PIG(Pipeline Inspection Gauge) is inserted in the pipeline and stores data of pipeline. In order to investigate the status of pipeline, a lot of sensors such as caliper, pressure, IMU and odometer are used. In this paper, the navigation storage data system for PIG is developed. It has master/slave structure for a real time operation. The master system stores data, while the slave system acquire the data from sensors. The performance of the developed system is verified by pull rig test.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2190-2192
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• 2001

가스 배관 진단 시스템은 배관 내부에 삽입되어 배관 내에 주입된 가스에 의해 추진되는 시스템으로 배관의 건설, 유지, 보수, 해체 등의 작업을 위한 여러 정보를 수집한다. 배관 진단을 위한 대표적인 센서로는 배관 내부의 찌그러짐(dent)과 주름(wrinkle)의 형태 및 크기를 측정하는 캘리퍼(caliper) 센서와 배관 외부의 파손을 측정하는 MFL(Magnetic Flus Leakage) 센서 그리고 배관 내의 환경 정보를 측정하기 위한 온도 센서와 압력 센서가 있다. 이러한 센서들로 수집된 정보를 활용하기 위해서는 정확한 위치 정보가 필요하므로 IMU(Inertial Measurement Unit)와 주행 거리계를 사용하는 결합 항법 시스템도 필요하다. 본 논문에서는 가스 배관 진단 시스템을 위한 항법 데이터 저장 시스템을 개발한다. 배관 진단 시스템의 특성상 일반적인 측정 센서는 700Hz 이상의 주기로 측정되고 항법 정보는 100Hz 주기 이상으로 측정되며 배관 내 이동 시간은 2시간에서 24시간 이상으로 다양하므로 많은 데이터를 효율적으로 저장할 수 있어야 한다. 따라서 데이터 저장 장치로는 DAT를 사용하게 되며 많은 센서 데이터를 실시간으로 저장하기 위해서 마스터-슬레이브 구조를 갖는 멀티 프로세서 구성을 이용한 항법 데이터 저장 시스템을 설계 제작하였다.