• Journal of Ocean Engineering and Technology
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• v.22 no.4
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• pp.106-113
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• 2008

This paper presents an underwater navigation system based on range measurements from a known reference station fixed on the sea bottom or floated at surface with a buoy, for which the system is extended to 3-dimensional coordinates. We formulated a state equation in polar coordinates and constituted an extended Kalman filter for discrete-time implementation of the navigation algorithm. The autonomous underwater vehicle, lSiMl, cruising with a constant speed can estimate its trajectory using just range measurements and additional depth, heading and pitch sensors. Simulation studies were performed to evaluate the underwater navigation of the maneuvering AUV with range measurements. We modulated the sample rate of range measurements to evaluate the effect of the update rate, and changed the initial position error of the AUV to check the robustness to estimation errors. Simulation results illustrates that the extended navigation system provides convergence of the state estimates. The navigation system was conditionally stable when it had initial position errors.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.760-767
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• 2013

In this paper, we developed a Manta-type AUV (Autonomous Underwater Vehicle) and analyzed its control performance as well as its dynamic characteristics underwater. The nonlinear motion of equations, which are expressed in terms of hydrodynamic coefficients obtained by various experiments, are used to simulate the motion of a Manta AUV underwater. We applied the sliding-mode theory to control the heading angle and depth of the vehicle, and confirmed the effectiveness of the control algorithm through simulations and sea-trials.

• Journal of Ocean Engineering and Technology
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• v.11 no.1
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• pp.106-112
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• 1997

This paper describes the development of a test-bed vehicle named TAUV which can be a tool to evaluate the performance of a new control algorithm, operating software and the characteristics of sensors for an AUV. The test-bed AUV is designed to operate at depth of ten meters. It is 19.5kg in air and neural buoyancy in water and the dimension is $535{\times}400{\times}102mm$. TAUV is equipped with a magnetic compass, a biazial inclinometer, a rate gyro, a pressure sensor and an altitude sonae for measuring the motion of the vehicle. Two horizoltal thursters and two elevators are installed in order to propel and control the AUV. This paper persents the control system of TAUV which is based on a 16 bit single-chip microprocessor, 80c196kc, and the software architecture for the operating system. Experimental results are included to verify the performance of the TAUV.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.109.5-109
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• 2002

Autonomous underwater vehicles (AUVs) are unmanned underwater vessels to investigate sea environments, oceanography and deep-sea resources autonomously. Docking systems are required to increase the capability of the AUVs to recharge the batteries and to transmit data in real time in underwater. This paper presents a visual servo control system for an AUV to dock into an underwater station with a camera. To make the visual servo control system , this paper derives an optical flow model of a camera mounted on an AUV, where a CCD camera is installed at the nose center of the AUV to monitor the docking condition. This paper combines the optical flow equation of the camera with the AUV's equation o...

• Journal of the Korean Society of Industry Convergence
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• v.21 no.6
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• pp.389-394
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• 2018

Remotely operated vehicle(ROV) and autonomous underwater vehicle(AUV) have been used for underwater surveys, underwater exploration, resource harvesting, offshore plant maintenance and repair, and underwater construction. It is hard for people to work in the deep sea. Therefore, we need a vision control system of underwater submersible that can replace human eyes. However, many people have difficulty in developing a deep-sea image control system due to the deep sea special environment such as high pressure, brine, waterproofing and communication. In this paper, we will develop an Ethernet based remote image control system that can control the image mounted on ROV.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.406-413
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• 2007

This paper proposes a self-recurrent wavelet neural network(SRWNN) based adaptive backstepping control technique for the robust steering control of autonomous underwater vehicles(AUVs) with unknown model uncertainties and external disturbance. The SRWNN, which has the properties such as fast convergence and simple structure, is used as the uncertainty observer of the steering model of AUV. The adaptation laws for the weights of SRWNN and reconstruction error compensator are induced from the Lyapunov stability theorem, which are used for the on-line control of AUV. Finally, simulation results for steering control of an AUV with unknown model uncertainties and external disturbance are included to illustrate the effectiveness of the proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.6
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• pp.614-619
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• 2015

In this study, a dynamics model was developed to predict the motion performance of an Autonomous Underwater Vehicle (AUV). The dynamics model includes basic dynamic state variables of the hull and force terms to determine the motion of the AUV. The affecting terms for the forces are hydrostatic force, added mass, hydrodynamic damping, lift and drag forces. The force terms can be calculated using analytical and Computational Fluid Dynamics methods. For the underwater motion simulation, a simple PD controller was used. Also, the AUV was tested in a water tank and near sea for the partial verification of the fluid drag force coefficients and way-point tracking motions.

• International Journal of Ocean System Engineering
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• v.1 no.2
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• pp.60-67
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• 2011

This paper presents an in-situ correction method to compensate for the position error of an autonomous underwater vehicle (AUV) near the sea floor. AUVs generally have an inertial navigation system assisted with auxiliary navigational sensors. Since the inertial navigation system shows drift in position without the bottom reflection of a Doppler velocity log, external acoustic positioning systems, such as an ultra short baseline (USBL), are needed to set the position without surfacing the AUV. The main concept of the correction method is as follows: when the AUV arrives near the sea floor, the vehicle moves around horizontally in a circular mode, while the USBL transceiver installed on a surface vessel measures the AUV's position. After acquiring one data set, a least-square curve fitting method is adopted to find the center of the AUV's circular motion, which is transferred to the AUV via an acoustic telemetry modem (ATM). The proposed method is robust for the outlier of USBL, and it is independent of the time delay for the data transfer of the USBL position with the ATM. The proposed method also reduces the intrinsic position error of the USBL, and is applicable to the in-situ calibration as well as the initialization of the AUVs' position. Monte Carlo simulation was conducted to verify the effectiveness of the method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.513-517
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• 2006

Autonomous Underwater Vehicles plays specific role in underwater investigation. Generally, this kind of vehicles will move along a planned path for sea bottom or underwater installations inspections, search for mineral deposits along shelves, seeking lost items including bottom mines or for hydrographic measurements. A crucial barrier for it remains the possibility of precise determination of their underwater position. Commonly used radionavigation systems do not work in such circumstances or do not guarantee the required accuracies. In the paper some new solution is proposed on the assumption that it is possible to increase the precision by certain processing of a combination of measurements conducted by means of different techniques. Objective of the paper is the idea of navigation of AUV which consists of two phases: firstly a trip of AUV along pre-planned route and after that postprocessed transformation of collected data in post-processing mode. During the processing of collected data the modern adjustment methods have been applied, mainly estimation by means of least squares and M-estimation. Application of these methods should be associated with the measuring and geometric conditions of navigational tasks and thus suited for specific scientific and technical problems of underwater navigation. The first results of computer aided investigation will be presented and the basic scope of these application and possible development directions will be indicated also. The paper is prepared as an partial results of the works carried out within a framework of the research Project: 'Improvement of the Precise Underwater Vehicle Navigation Methods' financed by the Polish Ministry of Education and Science (No 0 T00A 012 25).

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.194-200
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• 2016

Recently, UUVs (unmanned underwater vehicles) have increasingly been applied in various science and engineering applications. In-water inspection, which used to be performed by human divers, is a potential application for UUVs. In particular, the operational safety and performance of in-water inspection missions can be greatly improved by using an underwater robotic vehicle. The capabilities of hovering maneuvers and automatic image mosaicking are essential for autonomous underwater visual inspection. This paper presents the development of a hover-capable autonomous underwater vehicle system for autonomous in-water inspection, which includes both a hardware platform and operational software algorithms. Some results from an experiment in a model basin are presented to demonstrate the feasibility of the developed system and algorithms.