• International Journal of Ocean System Engineering
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• v.1 no.2
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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 Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.67-73
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• 2023

As interest in underwater structures and ocean exploration increases, many researchers are proposing methods for modeling and controlling various remotely operated vehicles (ROVs). Recently, hybrid systems composed of an autonomous underwater vehicle and an ROV capable of remote control and autonomous navigation are being developed. In this study we introduce a method that models Ariari-aROV, an ROV consisting of five thrusters, and performs navigation. The proposed ROV can be controlled manually and by autonomous navigation when given a target point. An extended Kalman filter is utilized for sensor measurement correction for more precise navigation. The proposed method is verified through a simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.349-355
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• 2015

Underwater robots generally show better performances for tasks than humans under certain underwater constraints such as. high pressure, limited light, etc. To properly diagnose in an underwater environment using remotely operated underwater vehicles, it is important to keep autonomously its own position and orientation in order to avoid additional control efforts. In this paper, we propose an efficient method to assist in the operation for the various disturbances of a remotely operated vehicle for the diagnosis of underwater structures. The conventional AHRS-based bearing estimation system did not work well due to incorrect measurements caused by the hard-iron effect when the robot is approaching a ferromagnetic structure. To overcome this drawback, we propose a sensor fusion algorithm with the camera and AHRS for estimating the pose of the ROV. However, the image information in the underwater environment is often unreliable and blurred by turbidity or suspended solids. Thus, we suggest an efficient method for fusing the vision sensor and the AHRS with a criterion which is the amount of blur in the image. To evaluate the amount of blur, we adopt two methods: one is the quantification of high frequency components using the power spectrum density analysis of 2D discrete Fourier transformed image, and the other is identifying the blur parameter based on cepstrum analysis. We evaluate the performance of the robustness of the visual odometry and blur estimation methods according to the change of light and distance. We verify that the blur estimation method based on cepstrum analysis shows a better performance through the experiments.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.319-321
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• 2007

This paper introduces a general overview of the 6000m class deep-sea ROV. Hemire and Henuvy. and then describes its motion control system. It is developed by Korea Ocean Research & Development Institute(KORDI) for 6 years since 2001. sponsored by the Ministry of Maritime Affairs and, Fisheries (MOMAF). Hemire is remotely operated by a fiber optic telemetry. where 6 thrusters are controlled by operator in manual mode and by auto depth control and auto heading control in auto mode. In this paper. operational mechanism of manual and automatic mode with some convenient functions for operator is desc.ribed. Finally, results of sea trial conducted at the Philippine sea where a depth is 5.770m are shown.

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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• pp.180-193
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• 2020

In this study, the end-effector tracking performance of a manipulator installed on a remotely operated vehicle (ROV) for autonomous underwater intervention is verified. The underwater manipulator is an ARM 7E MINI model produced by the ECA group, which consists of six joints and one gripper. Of the six joints of the manipulator, two are revolute joints and the other four are prismatic joints. Velocity control is used to control the manipulator with forward and inverse kinematics. When the manipulator approaches a target object, it is difficult for the ROV to maintain its position and posture, owing to various disturbances, such as the variation in both the center of mass and the reaction force resulting from the manipulator motion. Therefore, it is necessary to compensate for the influences and ensure the relative distance to the object. Simulations and experiments are performed to track the trajectory of a virtual object, and the tracking performance is verified from the results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.423-436
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• 2003

Submarine optical fiber cable construction consists of marine survey, PLGR(Pre Lay Grapnel Run), shore-end-work, laying order. PLGR is the work process which removes the oceanic contaminations(ropes, wires, nets etc.) in the route before laying the submarine optical cable. This PLGR is work to ease the cable lay safely in seabed, improve the performance of Plough and ROV((Remotely-Operated Vehicle) laying work, and protect laying equipment. This paper presents the optimization algorithm implementation of KP(Kilometer Post) and XTE(Cross Track Error) to manage marine survey and PLGR work efficiently. In this paper, we composes overall PLGR work, and proposed optimization algorithm of KP and XTE. For the validity evaluation of this paper, KP and XTE decision algorithm are implemented and tested.

• Journal of Ocean Engineering and Technology
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• v.22 no.6
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• pp.64-74
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• 2008

The flaw around a ROV (Remotely Operated Vehicle) has been numerically investigated to improve resistance performance by modifying the hull form of the ROV. For the base hull form considered in this study, the form drag rather than the friction drag is dominant to the total drag Subsequently, the surfaces on which the local pressure highly acts have been modified to produce the streamlined-shape. Based on the surface modification, seven different hull forms have been chosen as candidates for drag reduction. Among the candidates, the semi-sphericalized housing and the streamlined-bow achieved greatest drag reduction comparing with the others. Consequently, the hull form combined with the semi-sphericalized housing and the streamlined-bow gave approximately 17% drag reduction at the design velocity of 3 knots.

• Journal of Ship and Ocean Technology
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• v.11 no.1
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• pp.36-46
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• 2007

The maintenance of a ship is essential for safe navigation and hence regular surveys are prescribed according to the rule of classification societies. A hull inspection is generally performed by professional divers, but it takes a long time and the efficiency is low in terms of time and cost. In this research, a ROV(Remotely Operated Vehicle) named as SNU-ROV(Seoul National University-ROV) is developed to replace the conventional inspection method. In this system, the ROV is intended to be used for inspecting ship and harbor because harbor inspection is merging as a safety measure against any possible terror actions. In order to increase the efficiency of inspection, the ROV must be able to measure the exact position of damages. SNU-ROV has a positioning system based on LBL(Long Base Line). In shallow water such as harbor, however, LBL has bad DOP(Dilution of Precision) in the depth direction due to the limited depth. Thus LBL only can not locate the exact depth position. To solve the DOP problem, a pressure sensor is introduced to LBL and a complementary filter is attached by using indirect feedback Kalman filter. Thus developed positioning system is verified by simulation and experiment in towing tank.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.460-470
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• 2011

This paper presents a dynamic workspace control method of underwater manipulator considering a floating ROV (Remotely Operated vehicle) motion caused by sea wave. This method is necessary for the underwater work required linear motion control of a manipulator's end-effector mounted on a floating ROV in undersea. In the proposed method, the motion of ROV is modeled as nonlinear first-order differential equation excluded dynamic elements. For online manipulator control achievement, we develop the position tracking method based on sensor data and EKF (Extended Kalman Filter) and the input velocity compensation method. The dynamic workspace control method is established by applying these methods to differential inverse kinematics solution. For verification of the proposed method, experimental data based test of ROV position tracking and simulation of the proposed control method are performed, which is based on the specification of the KORDI deep-sea ROV Hemire.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.813-821
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• 2013

In this paper, we present the development of P-SURO II hybrid AUV (Autonomous Underwater Vehicle) which can be operated in both of AUV and ROV (Remotely Operated Vehicle) modes. In its AUV mode, the vehicle is supposed to carry out some of underwater missions which are difficult to be achieved in ROV mode due to the tether cable. To accomplish its missions such as inspection and maintenance of complex underwater structures in AUV mode, the vehicle is required to have high level of autonomy including environmental recognition, obstacle avoidance, autonomous navigation, and so on. In addition to its systematic development issues, some of algorithmic issues are also discussed in this paper. Various experimental studies are also presented to demonstrate these developed autonomy algorithms.