• 한국해양공학회지
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• 제28권6호
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• pp.566-573
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• 2014

This paper presents the results of an integrated navigation performance analysis for selecting the sensor of an unmanned underwater vehicle (UUV) using Monte Carlo numerical simulation. An inertial measurement unit (IMU) and Doppler velocity log (DVL) are considered to build the integrated navigation system. The position error and price of the sensor are selected as performance indices to evaluate the volunteer integrated navigation systems. Monte-Carlo simulation is introduced to analyze the circular error probability (CEP) and its variance. Simulation results provide the proper sensor combination for integrated navigation in relation to the performance and price.

• International Journal of Ocean System Engineering
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• 제1권2호
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• pp.102-109
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• 2011

This paper describes the implementation of a precise underwater navigation solution using a multiple sensor fusion technique based on USBL, GPS, DVL and AHRS measurements for the operation of a remotely operated mine disposal vehicle (MDV). The estimation of accurate 6DOF positions and attitudes is the key factor in executing dangerous and complicated missions. To implement the precise underwater navigation, two strategies are chosen in this paper. Firstly, the sensor frame alignment to the body frame is conducted to enhance the performance of a standalone dead-reckoning algorithm. Secondly, absolute position data measured by USBL is fused to prevent cumulative integration error. The heading alignment error is identified by comparing the measured absolute positions with the DR algorithm results. The performance of the developed approach is evaluated with the experimental data acquired by MDV in the South-sea trial.

• Journal of Advanced Marine Engineering and Technology
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• 제37권6호
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• pp.644-652
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• 2013

본 논문은 만타형 무인잠수정의 개발과 실해역 성능시험에 관한 내용을 다룬다. 먼저 만타형 무인 잠수정의 운동성능을 예측하기 위한 시뮬레이션을 수행하였다. 시뮬레이션 결과를 통해서 만타형 잠수정의 운동성능을 검증하였으며 결과를 바탕으로 테스트베드인 만타형 무인잠수정을 설계하였다. 만타 잠수정은 자세 및 경로의 계측을 위하여 DVL (Doppler Velocity Log), Gyrocompass, GPS, 압력센서 등을 탑재하였으며 운항제어를 위한 추진기와 1개의 수직타 4개의 수평타를 장착하여 3자유도 운동이 가능하다. 실해역에서 운동성능시험과 자율운항 성능시험을 통해 만타형 무인잠수정 시스템을 검증하였다.

• 한국해양공학회지
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• 제24권3호
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• pp.46-51
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• 2010

This paper describes the implementation of a precise underwater navigation solution using a multi-sensor fusion technique based on USBL, DVL, and IMU measurements. To implement this precise underwater navigation solution, three strategies are chosen. The first involves heading alignment angle identification to enhance the performance of a standalone dead-reckoning algorithm. In the second, the absolute position is found quickly to prevent the accumulation of integration error. The third one is the introduction of an effective outlier rejection algorithm. The performance of the developed algorithm was verified with experimental data acquired by the deep-sea ROV, Hemire, in the East-sea during a survey of a methane gas seepage area at a 1,500 m depth.

• 로봇학회논문지
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• 제15권1호
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• pp.32-38
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• 2020

This paper describes a method for tracking attitude and position of underwater robots. Underwater work with underwater robots is subject to differences in work efficiency depending on the skill of the operator and the utilization of additional sensors. Therefore, this study developed an underwater robot that can operate autonomously and maintain a certain attitude when working underwater to reduce difference of work efficiency. The developed underwater robot uses 8 thrusters to control 6 degrees of freedom motion, IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and PS (Pressure Sensor) to measure attitude and position. In addition, the thruster allocation algorithm was designed to follow the control desired value using 8 thrusters, and the motion control experiments were performed in the engineering water basin using the thruster allocation method.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.702-708
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• 2013

Underwater TRN (Underwater Terrain Referenced Navigation) estimates an underwater vehicle state by measuring a distance between the vehicle and undersea terrain, and comparing it with the known terrain database. TRN belongs to absolute navigation methods, which are used to compensate a drift error of dead reckoning measurements such as IMU (Inertial Measurement Unit) or DVL (Doppler Velocity Log). However, underwater TRN is different to other absolute methods such as USBL (Ultra-Short Baseline) and LBL (Long Baseline), because TRN is independent of the external environment. As a magnetic-field-based navigation, TRN is a kind of geophysical navigation. This paper develops an EKF (Extended Kalman Filter) formulation for underwater TRN. A filter propagation part is composed by an inertial navigation system, and a filter update is executed with echo-sounder measurement. For large-initial-error cases, an adaptive EKF approach is also presented, to keep the filter be stable. At the end, simulation studies are given to verify the performance of the proposed TRN filter. With simplified sensor and terrain database models, the simulation results show that the underwater TRN could support conventional underwater navigation methods.

• 로봇학회논문지
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• 제9권1호
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• pp.28-38
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• 2014

This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(Monte Carlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty is not yet proved. Along with localization, the experiment also discloses the uncertainty features of the range measurement such as bias and variance. The proposed localization method rejects outlier range data and the experiment shows that outlier rejection improves localization performance. It is as expected that the proposed method doesn't yield as precise location as those methods which use high priced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy range sensors. However, it is noticeable that the proposed method can achieve the accuracy which is affordable for correction of accumulated dead reckoning error, even though it uses only range data of low reliability and accuracy.

• 전자공학회논문지
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• 제54권3호
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• pp.108-118
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• 2017

본 논문은 수중 로봇 항법에 사용하기 위한 영상 소나 기반 SLAM (simultaneous localization and mapping) 방법을 제안하고, 성능 평가를 위해 실제 로봇에 탑재하여 실험한 내용을 소개한다. 일반적인 수중 항법은 관성 센서에서 출력되는 정보를 바탕으로 로봇의 위치 및 자세(x,y,z,${\phi}$,${\theta}$,${\psi}$)를 추정한다. 하지만, 장시간 주행할 경우 위치 오차의 누적으로 인하여 정확도가 감소하게 된다. 이에 본 논문에서는 영상 소나로부터 얻을 수 있는 외부 정보를 바탕으로 관성 항법의 위치 추정 성능을 높이고 지도 작성을 수행할 수 있는 SLAM 방법을 제안하고자 한다. 영상 소나를 위한 인공 표식물과 확률 기반 물체 인식 구조를 통해 인공 표식물의 인식 성능을 높이고, 이를 통해 얻게 된 인공 표식물의 위치 정보를 활용하여 관성 항법의 누적 오차를 줄이고자 한다. 항법 알고리즘으로는 확장형 칼만 필터(Extended Kalman Filter, EKF)를 적용하여 로봇의 위치 및 자세를 추정하고 지도를 작성한다. 제안한 방법은 선박해양플랜트연구소에서 보유 중인 수중 로봇 'yShark'에 탑재하여 대형 수조에서 실시간 검증을 수행하였다.

• 한국정보통신학회논문지
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• 제24권11호
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• pp.1417-1423
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• 2020

본 논문에서는 수중에서 운동하는 무인잠수정의 경로점 유도법칙을 제안한다. 시선각 유도법칙과 수선경로 오차를 줄여가는 경로추종 유도법칙을 조합하여 효과적인 경로점 유도법칙을 설계하였고, 수선경로 오차의 거리에 따라 제어이득을 변화시켜 시스템의 안정성을 증가시켰다. 또한, 관성항법장치와 도플러속도계를 이용한 복합항법 시스템의 성능을 확인할 수 있는 HILS를 구성하였다. 같은 경로점 및 목표점을 입력 후 HILS 수행결과와 실해역 주행시험 결과를 비교하여, 제안한 유도법칙 및 HILS가 올바르게 구성되어 있음을 확인하였다.

• 한국해양공학회지
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• 제33권2호
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• pp.168-177
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• 2019

KRISO (Korea Research Institute of Ship & Ocean Engineering) started a project to develop the core algorithms for autonomous intervention using an underwater robot in 2017. This paper introduces the development of the robot platform for the core algorithms, which is an ROV (Remotely Operated Vehicle) type with one 7-function manipulator. Before the detailed design of the robot platform, the 7E-MINI arm of the ECA Group was selected as the manipulator. It is an electrical type, with a weight of 51 kg in air (30 kg in water) and a full reach of 1.4 m. To design a platform with a small size and light weight to fit in a water tank, the medium-size manipulator was placed on the center of platform, and the structural analysis of the body frame was conducted by ABAQUS. The robot had an IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and a depth sensor for measuring the underwater position and attitude. To control the robot motion, eight thrusters were installed, four for vertical and the rest for horizontal motion. The operation system was composed of an on-board control station and operation S/W. The former included devices such as a 300 VDC power supplier, Fiber-Optic (F/O) to Ethernet communication converter, and main control PC. The latter was developed using an ROS (Robot Operation System) based on Linux. The basic performance of the manufactured robot platform was verified through a water tank test, where the robot was manually operated using a joystick, and the robot motion and attitude variation that resulted from the manipulator movement were closely observed.