• Journal of the Society of Naval Architects of Korea
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• v.50 no.3
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• pp.190-198
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• 2013

In order to predict acoustic pressure distributions by exterior incident wave at Cylindrical Hydrophone Array (CHA) sensor's positions, acoustic pressure analysis is performed by using beam tracing method. Beam tracing method is well-known of reliable pressure analysis methods at high-frequency range. When an acoustic noise source is located at the center of rectangular room, acoustic pressure analysis is performed by using both beam tracing method and Power Flow Boundary Element Method (PFBEM). By comparing with results of beam tracing method and those of PFBEM, the accuracy of beam tracing method is verified. We develop the CHA pressure analysis program by verified beam tracing method. The developed software is composed of model input, sensor array creator, analysis option, solver and post-processor. We can choose a model option of 2D or 3D. The sensor array generator is connected to a sonar which is composed of center position, bottom, top and angle between sensors. We also can choose an analysis option such as analysis frequency, beam number, reflect number, etc. The solver module calculates the ray paths, acoustic pressure and result of generating beams. We apply the program to 2D and 3D CHA models, and their results are reliable.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.549-559
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• 2015

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.1-10
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• 2005

This paper presents a technique for localization of a mobile robot using a single ultrasonic sensor. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, corners and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD (Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a physically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.25-34
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• 2011

In this paper, we propose a new golf putting training system which we call "X-Putt". X-Putt analyzes putting strokes by measuring putter face angle and path. To do this, we improved the sonar-based localization scheme used by previous localization techniques. As a result, X-Putt can measure putter's location within the error range, ${\pm}0.9cm$ and putter face angle within ${\pm}1.5^{\circ}$. Additionally, we built an user application that has an easy-to-use interface for analyzing the strokes after training.

• The Journal of the Acoustical Society of Korea
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• v.26 no.1
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• pp.48-54
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• 2007

In this paper we have implemented a 3-D PL (Position Location) system to estimate the 3-dimensional position of a moving object in underwater environments. In this research, we let four sensors fixed in different Positions and moving sensorsto communicate with each other to find the 3-dementianal positions for both the fixed and moving objects. Using this we were also able to control the moving object remotely. When finding the position, we calculated the norm of the Jacobian matrix every iteration in the Newton algorithm. Also by using a different initial value for calculating the solution when the norm became higher than the critical value and the solution from the inverse matrix became unstable, we could find a more reliable position for the moving object. The proposed algorithm was used in implementing a DSP system capable of real-time position location. To verify the performance, experiments were done in a water tank. As a result we could see that our system could located the position of an object every 2 seconds with a error range of 5cm.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.