• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.214-220
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• 2016

Imaging sonars such as side-scanning sonar or forward-looking sonar are becoming fundamental sensors in the underwater robotics field. However, using sonar images for underwater perception presents many challenges. Sonar images are usually low resolution with inherent speckled noise. To overcome the limited sensor information for underwater perception, we investigated preprocessing methods for sonar images and feature detection methods for a nonlinear scale space. In this paper, we focus on a comparative analysis of (1) preprocessing for sonar images and (2) the feature detection performance in relation to the scale space composition.

• 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 Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.132-137
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• 2014

In this paper, An LQR controller is proposed for way-point tracking of AUV (Autonomous Underwater Vehicle). The LQR controller aims at tracking a series of way-points which operator registers arbitrarily in advance. It consists of a depth controller and a steering controller and AUV's surge speed is assumed varying to consider the dynamic environment of the underwater. In order to show the performance, a conventional state feedback controller is compared with the proposed controller by the simulation using Matlab/Simulink. The parameters of AUV developed by the author's laboratory are used. In the simulation, we verify that the LQR controller can track all the way-points within 1 m error range under the varying surge speed, which proves the robustness of the LQR controller.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.284-291
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• 2012

Recently, development of underwater robot has actively been in progress in the world as ROV(Remotely Operator Vehicle) and AUV(Autonomous Unmmanded Vehicle) style. But KIOST(Korea Institute of Ocean Science and Technology), beginning in 2010, launched the R&D project to develop the robot, dubbed CRABSTER(Crab + (Lob)ster) in a bid to enhance the safety and efficiency of resource exploration. CRABSTER has been designed to be able to walk and swim with its own legs without screws. Among many research subjects regarding CRABSTER, optimal swimming patterns are handled in this paper. In previous studies, drag forces during one period with different values for angle of each joint were derived. However kinematics of real-robot and fluid-dynamics are not considered. We conducted simulations with an optimization algorithm for swimming by considering simplified fluid dynamics in this paper. Drag-coefficients applied to the simulation were approximated values calculated by CFD(Computational Fluid Dynamics : Tecplot 360, ANSYS). In addition, optimized swimming patterns were applied to a real robot. The experiments with the real robot were conducted in circumstances in the water. As a result, when the experiments were carried out in the water, a regular pattern of drag force output came out depending on the movement of the robot. We confirmed the fact that the drag forces from the simulation and the experiment has a high similarity.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.805-812
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• 2013

This paper describes the design, control, and localization which comprise major aspects of the development of underwater robots for the mine disposal. The developed robots are called the Mine Killer (MK-1) and MK-2. MK-1 had been developed from September 2009 and was presented at the 9-th International Symposium at NPS Monterey CA, on May 17-21, 2010[1]. The paper presents design of MK-1 and MK-2 in detail with comparison of these two versions of MKs. Then it derives hydrodynamic coefficients of MK-1. Based on the coefficients, the motion of MK-1 is simulated for straight line motion and circular motion. Also simulation results for PD control, LQ control and sliding mode control are presented. Finally, it shows a particle filter method for localization of MK-1 and MK-2 using simple range data from acoustic beacons.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.45-55
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• 1998

In this paper, a robust path tracker and depth controller of Autonomous Underwater Vehicle based on sliding mode control is presented. We have also designed augmented equivalent control inputs by analyzing the sliding mode with the reaching mode. This can enhance the reaching rate, and improve chattering problems, that is, noise caused by the control plane actuator of the vehicle, which is one of the problems that occur when sliding mode control is used. Also to resolve the steady state error generated in the path tracker under current effect, a modified sliding plane is constructed. Also a redesigned sliding plane and control input using transformation matrix is proposed to do easy design of MIMO depth controller. For state variables that cannot be measured directly, reduced order sliding mode control is used to design an observer. The performance of designed path tracker and depth controller is investigated by computer simulation. The results show that the proposed control system has robust performance to parameter variation, modelling error and disturbance.

• The Journal of Korea Robotics Society
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• v.9 no.1
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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.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.374-383
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• 2004

This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

• International Journal of Ocean System Engineering
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• v.1 no.3
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• pp.120-135
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• 2011

This paper proposes a model based trajectory tracking control scheme for under-actuated underwater robotic vehicles. The difficulty in stabilizing a non-linear system using smooth static state feedback law means that the design of a feedback controller for an under-actuated system is somewhat challenging. A necessary condition for the asymptotic stability of an under-actuated vehicle about a single equilibrium is that its gravitational field has nonzero elements corresponding to non-actuated dynamics. To overcome this condition, we propose a continuous time-varying control law based on the direct estimation of vehicle dynamic variables such as inertia, damping and Coriolis & centripetal terms. This can work satisfactorily under commonly encountered uncertainties such as an ocean current and parameter variations. The proposed control law cancels the non-linearities in the vehicle dynamics by introducing non-linear elements in the input side. Knowledge of the bounds on uncertain terms is not required and it is conceptually simple and easy to implement. The controller parameter values are designed using the Taguchi robust design approach and the control law is verified analytically to be robust under uncertainties, including external disturbances and current. A comparison of the controller performance with that of a linear proportional-integral-derivative (PID) controller and sliding mode controller are also provided.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.51-59
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• 2016

In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.