• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.676-681
• /
• 2013

For underwater vehicles, the use of sensors such as cameras and laser scanners is limited by the difference in environment compared to robots designed to work on dry land. In underwater environments, if use is made of sound signals, valuable information can be obtained. The most important application is the localization of underwater sound sources. The estimated location of a sound source can be used to control underwater robots or submarines. Thus, the purpose of this research is to estimate the source's direction and location in a noisy underwater environment. The direction of the sound source is obtained using two hydrophones. Furthermore, if we assume that the robot or sound source is moving, the location of the sound source is estimated using more than two estimated directions. The feasibility of the developed algorithm is examined by experiments in a water tank and in the ocean.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2006.11a
• /
• pp.355-358
• /
• 2006

An underwater mooing target position tracking system using image tracking system of CPMC is developed to use in a test basin. Generally the performance tests of Autonomous Underwater Vehicles(AUVs) are conducted in the sea. Some efforts to perform the test in a test basin are exist, because the real sea tests need much time and manpower. And also the real sea tests are high cost. There is a restriction to acquire the position of AUVs using sonar sensor system in the test tank, because many sound reflecters are exist in a test basin. In this paper a position tracking system for underwater mooing target developed to break though this restriction. A Tank-test is conducted to examine the performance of the position tracking system.

• The Journal of Korea Robotics Society
• /
• v.12 no.4
• /
• pp.402-410
• /
• 2017

Acoustic based localization is essential to operate autonomous robotic systems in underwater environment where the use of sensorial data is limited. This paper proposes a localization method using artificial underwater acoustic sources. The proposed method acquires directional angles of acoustic sources using time difference of arrivals of two hydrophones. For this purpose, a probabilistic approach is used for accurate estimation of the time delay. Then, Gaussian sum filter based SLAM technique is used to localize both acoustic sources and underwater vehicle. It is performed by using bearing of acoustic sources as measurement and inertial sensors as prediction model. The proposed method can handle directional ambiguity of time difference based source localization by generating Gaussian models corresponding to possible locations of both front and back sides. Through these processes, the proposed method can provide reliable localization method for underwater vehicles without any prior information of source locations. The performance of the proposed method is verified by experimental results conducted in a real sea environment.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37C no.12
• /
• pp.1328-1336
• /
• 2012

Compared to terrestrial RF communications, underwater acoustic communications have several limitations such as limited bandwidth, high level of fading effects, and a large underwater propagation delay. In this paper, in order to tackle those limitations of underwater communications and to make it possible to form a large underwater monitoring systems, we propose a hierarchical underwater network architecture, which consists of underwater sensors, clusterheads, underwater/surface sink nodes, autonomous underwater vehicles (AUVs). In the proposed architecture, for the maximization of packet delivery ratio and the minimization of underwater sensor's energy consumption, a hybrid routing protocol is used. More specifically, cluster members use Tree based routing to transmit sensing data to clusterheads. AUVs on optimal trajectory movements collect the aggregated data from clusterhead and finally forward the data to the sink node. Also, in order to minimize the maximum travel distance of AUVs, an Integer Linear Programming based algorithm is employed. Performance analysis through simulations shows that the proposed architecture can achieve a higher data delivery ratio and lower energy consumption than existing routing schemes such as gradient based routing and geographical forwarding. Start after striking space key 2 times.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.4
• /
• pp.441-447
• /
• 2012

This paper presents a design technique of a Takagi-Sugeno (T-S) fuzzy-model-based $H_{\infty}$ controller for autonomous underwater vehicles (AUVs). The design procedure aims to render the stabilizing controller which satisfies performance of the diving control for AUVs in the presence of the disturbance. A nonlinear AUV is modeled by the T-S fuzzy system through the sector nonlinearity. By using Lyapunov function, the sufficient conditions are derived to guarantee the performance of robust depth control in the format of linear matrix inequality (LMI). To succeed for diving control of AUV, we add the constraints on the diving and pitch angles in the LMI conditions. Through the simulation, we confirm the effectiveness of the proposed methodology.

• Journal of Ocean Engineering and Technology
• /
• v.19 no.6 s.67
• /
• pp.78-85
• /
• 2005

Initial alignment and localization are important topics in inertial navigation systems, since misalignment and initial position error wholly propagate into the navigation systems and deteriorate the performance of the systems. This paper presents the error convergence characteristics of the hybrid navigation system for underwater vehicles initial position, which is based on an inertial measurement unit (IMU) accompanying a range sensor. This paper demonstrates the improvement on the navigational performance oj the hybrid system with the range information, especially focused on the convergence of the estimation of underwater vehicles initial position error. Simulations are performed with experimental data obtained from a rotating ann test with a fish model. The convergence speed and condition of the initial error removal for random initial position errors are examined with Monte Carlo simulation. In addition, numerical simulation is conducted with an AUV model in lawn-mowing survey mode to illustrate the error convergence of the hybrid navigation System for initial position error.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2002.05a
• /
• pp.243-250
• /
• 2002

According to Ocean Korea 21, a basic plan established by the Ministry of Maritime Affairs and Fisheries (MOMAF) of Korea in May 2000, Korea Research Institute of Ships and Ocean Engineering (KRISO) proposed a program for the development of a deep-sea unmanned underwater vehicle (UUV) to explore deep sea for scientific purpose. KRISO has launched a project in May 2001 under the support of MOMAF. The deep-sea unmanned underwater vehicle will be applied to scientific researches in deep-sea as well as in shallow water. For operation of underwater vehicles in shallow water near the Korean Peninsula, a special design is required because of strong tidal current. In addition, MOMAF requires the vehicle to be designed for the purpose of long range survey, a long-term observation, and precise works in a specific area. Thus, KRISO has planned to design the system with the functional combination of both ROV and AUV. This paper presents the design of the deep-sea unmanned underwater vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.1
• /
• pp.239-260
• /
• 2023

The underwater acoustic wireless communication networks are generally formed by the different autonomous underwater acoustic vehicles, and transceivers interconnected to the bottom of the ocean with battery deployed modems. Orthogonal frequency division multiplexing (OFDM) has become the most popular modulation technique in underwater acoustic communication due to its high data transmission and robustness over other symmetrical modulation techniques. To maintain the operability of underwater acoustic communication networks, the power consumption of battery-operated transceivers becomes a vital necessity to be minimized. The OFDM technology has a major lack of peak to average power ratio (PAPR) which results in the consumption of more power, creating non-linear distortion and increasing the bit error rate (BER). To overcome this situation, we have contributed our symmetry research into three dimensions. Firstly, we propose a machine learning-based underwater acoustic communication system through long short-term memory neural network (LSTM-NN). Secondly, the proposed LSTM-NN reduces the PAPR and makes the system reliable and efficient, which turns into a better performance of BER. Finally, the simulation and water tank experimental data results are executed which proves that the LSTM-NN is the best solution for mitigating the PAPR with non-linear distortion and complexity in the overall communication system.

• Journal of computational fluids engineering
• /
• v.20 no.2
• /
• pp.81-87
• /
• 2015

For Underwater vehicles, Unwanted roll excursions are inevitable as they are caused by induced propeller torque, disturbances, and banking motion during turns. To estimate the manoeuvring performance of underwater vehicle, it is necessary to obtain the roll coefficient of body. This paper was covered estimation of roll coefficient of underwater vehicle using STAR-CCM+, commercial CFD(Computational Fluid Dynamics) code. The RANS equations for incompressible fluid flows was solved numerically by using a finite volume method. An MRF(Moving Reference Frame) Method was Also adopted for rotations of body. For the validation, the flow around a DARPA SUBOFF bare hull model was simulated and good agreement with experiments was obtained. And Pure roll coefficients were calculated and campared with the experimental data which were presented by Seoul National University. Finally, an underwater vehicle model with propeller was simulated and analyzed for estimation of roll coefficient variation caused by induced propeller torque.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.682-687
• /
• 2013

Navigation is a crucial capability for all types of manned or unmanned vehicles. However, vehicle navigation in underwater environments still remains a challenging problem since GPS signals for position fixes are not available in the water. Terrain-referenced underwater navigation is an alternative navigation technique that utilizes geometric information of the subsea terrain to correct drift errors due to dead-reckoning or inertial navigation. Terrain-referenced navigation requires the description of an undulating terrain surface as a mathematical function or table, which often leads to a highly nonlinear estimation problem. Recently, PFs (Particle Filters), which do not require any restrictive assumptions about the system dynamics and uncertainty distributions, have been widely used for nonlinear filtering applications. However, PF has considerable computational requirements which used to limit its applicability to problems of relatively low state dimensions. This study proposes the use of a Rao-Blackwellized particle filter that is computationally more efficient than the standard PF for terrain-referenced underwater navigation involving a moderate number of states, and its performance is compared with that of the extended Kalman filter algorithm. The validity and feasibility of the proposed algorithm is demonstrated through numerical simulations.