• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.3
• /
• pp.808-814
• /
• 2010

In this paper we executed a SBL(Short Baseline) underwater acoustic positioning system that is a kind of underwater position estimation system to estimates the 3-dimensional position of ROV(Remotely Operated Vehicle) using hydrophones and DAQ(Data Acquisition) system in the basin which dimensions are $3{\times}3{\times}1.7(m)$. For this experiment, we let 4 hydrophones in different positions of the basin for receiver and 1 hydrophone is fixed on the underwater vehicle for transmitting sensor(pinger). These five hydrophones are communicated with each other to find the 3-D positions of the moving ROV in the basin. The measured signals are collected by DAQ system and the positions of the ROV are plotted by LabView program in real-time. To estimate the position of the ROV we used a trigonometric method. In X and Y plane the estimated data has a small errors but in Z plane the estimated data has large errors so we cannot use this data for position control. One solution of this problem is using depth sensor that implemented of the underwater vehicle. Hereafter, we will test in the ocean using designed SBL system.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2003.05a
• /
• pp.94-98
• /
• 2003

Remotely Operated Vehicle. ROV is a new concept equipment being made to replace the manned systems for investigating the deep sea environment. This paper presents the dynamic cable response during ROV launching considering the coupling effects of ship motion. By the harmonic response analysis, the variations of cable tensions were obtained. Harmonic forces in head/beam sea states were calculated by the concept of relative acceleration which obtained by ship motion analysis.

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

• Journal of the Society of Naval Architects of Korea
• /
• v.45 no.6
• /
• pp.579-589
• /
• 2008

In the past few years, there are many studies and researches of the underwater vehicles which are carried out its mission using sonar sensors. MSCL(Marine System Control Lab.) at Inha University developed test-bed small ROV, ISRO. ISRO is an open-frame type and has 4 thrusters. ISRO can control 4 motions i.e surge, sway, yaw and heave with sonar sensors. ISRO is developed for inspection of ship hull, marine structure, plant of lake or river and so on. When ROV ISRO inspects something, it is necessary to control the position of ROV ISRO's for the movement and anti-collision with structures in the underwater. In this paper, we deal with the development of a small ROV and verification of the position control system via simulation and experiment using sonar sensors.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.5
• /
• pp.454-461
• /
• 2019

In autonomous interventions using an underwater vehicle with a manipulator, grasping based on target detection and recognition is one of the core technologies. To complete an autonomous grasping task, the vehicle body approaches the target closely and then holds it through operating the end-effector of the manipulator, while the vehicle maintains its position and attitude without unstable motion. For vehicle motion control, it is very important to identify the hydrodynamic parameters of the underwater vehicle, including the propulsion force. This study examined the propulsion characteristics of the autonomous intervention ROV developed by KRISO, because there is a difference between the real exerted force and the expected force. First, the mapping between the input signal and thrusting force for each underwater thruster was obtained through a water tank experiment. Next, the real propulsion forces and moments of the ROV exerted by thrusting forces were directly measured using an F/T (force/torque) sensor attached to the ROV. Finally, the differences between the measured and expected values were confirmed.

• Journal of Advanced Research in Ocean Engineering
• /
• v.3 no.3
• /
• pp.136-148
• /
• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

• Ocean Systems Engineering
• /
• v.1 no.3
• /
• pp.195-205
• /
• 2011

A method for calibrating a laser profiling system for seafloor micro-topography measurements is described. The system consists of a digital camera and an arrangement of six red lasers that are mounted as a unit on a remotely operated vehicle (ROV). The lasers project as parallel planes onto the seafloor, creating profiles of the local topography that are interpreted from the digital camera image. The goal of the calibration was to determine the plane equations for the six lasers relative to the camera. This was accomplished in two stages. First, distortions in the digital image were corrected using an interpolation method based on a virtual pinhole camera model. Then, the laser planes were determined according to their intersections with a calibration target. The position and orientation of the target were obtained by a registration process. The selection of the target shape and size was found to be critical to a successful calibration at sea, due to the limitations in the manoeuvrability of the ROV.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.28 no.3
• /
• pp.252-261
• /
• 1992

The accuracy of the position fixing with telemetry techniques depends in general on the accuracy of the location of the receiving point(hydrophone). To increase the accuracy of the coordinates of four hydrophones suspended down at both sides of the vessel anchored, each hydrophone motion is compensated using a depth pinger mounted on the seabed of 30m depth. The pinger location is calculated with a hyperbolic method. Using this technique so called hydrophone coordinates calibration, the movement of the Remotely Operated Vehicle(ROV), which has the same type of pinger mentioned above could be tracked down more accurately. Under the maximum variation ranges of a hydrophone of 5.2m in athwartships, 3.2m in alongship, and about 0.2m/s of the moving velocity in both directions, the ROV track with calibration is more close to the reality than that without calibration Tow depth pingers of same frequency can be distinguished by the use of three factors; The pulse period, the phase and the pulse period variation allowed in acquisition of the pinger as far as its pulse period is varied in smooth.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.3
• /
• pp.289-299
• /
• 2019

Various sizes of ROVs are being utilized in offshore industrial, scientific, and military applications all around the world. Because of innovative developments in science and technology, image acquisition devices such as sonar devices and cameras have been reduced in size and their performance has been improved. Thus, we can expect better accuracy and higher resolution even in the case of exploration using a small ROV. The purpose of this paper is to prepare a standard procedure for the identification of unidentified hazardous materials found during the National Oceanographic Survey. In this paper, we propose an IDEF (Integrated DEFinition) method modeling technique to identify unidentified targets using a small ROV. In accordance with the proposed procedure, an ROV survey was carried out on target No.16 with a four-ton-class fishing boat as a support vessel on September 18th of 2018 in the sea near Daebu Island. Unidentified targets, which were not known by the multi-beam data obtained from the ship, could be identified as concrete pipes by analyzing the HD camera and high-resolution sonar images acquired by the ROV. The whole proposed procedure could be verified, and the survey with the small ROV required about 10 days to identify the target in one place.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.3
• /
• pp.300-311
• /
• 2019

An ROV trencher is a type of heavy-duty work class ROV equipped with high-pressure water jet tools for cutting into the sea floor and burying cables. This kind of trencher is mostly used for PLIB operations. This paper introduces the development of this kind of ROV trencher, which has a 698 kW power system, with a 250 kW hydraulic system and two 224 kW water jet systems. The project was launched in January 2014. After four years of design, manufacturing, and system integration, we carried out two sea trials near the Yeongilman port (about 20-30 m in depth) in Pohang to evaluate the system performance in November 2017 and August 2018. Through tests, we found that most of specifications were satisfied, including a maximum bury depth of 3 m, maximum bury speed of 2 km/h, and maximum forward speed of 1.54 m/s.