• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.244-253
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• 2022

Recently, installation projects of structures such as offshore wind farms have been increasing, and the installation of such marine obstacles could affect ships that pass nearby. Therefore, the purpose of this study was to quantitatively evaluate the risk posed to passing ships due to obstacles in their passage. Hence, parameters that affected the risk were selected, and scenarios were set based on the parameters. The scenarios were evaluated through the ES model, which is a risk assessment model, and we confirmed that the risk ratio increased as the size of the obstacle increased, the safe distance from the obstacle increased, the speed of ship decreased, and the traffic volume increased. Additionally, we found that when the traffic flow direction was designated, the risk ratio was lower than that of general traffic flow. In this study, we proposed a generalization model based on the results of the performed scenarios, applied it to the Dadaepo offshore wind farm, and demonstrated that the estimation of the approximate risk ratio was possible through the generalization model. Finally, we judged that the generalization model proposed in this study could be used as a preliminary reference for the installation of marine obstacles.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.141-147
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• 2008

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.47-54
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• 2022

For safe driving of autonomous vehicles, road damage detection is very important to lower the potential risk. In order to ensure safety while an autonomous vehicle is driving on the road, technology that can cope with various obstacles is required. Among them, technology that recognizes static obstacles such as poor road conditions as well as dynamic obstacles that may be encountered while driving, such as crosswalks, manholes, hollows, and speed bumps, is a priority. In this paper, we propose a method to extract similarity of images and find damaged road images using OpenCV image processing and CNN algorithm. To implement this, we trained a CNN model using 280 training datasheets and 70 test datasheets out of 350 image data. As a result of training, the object recognition processing speed and recognition speed of 100 images were tested, and the average processing speed was 45.9 ms, the average recognition speed was 66.78 ms, and the average object accuracy was 92%. In the future, it is expected that the driving safety of autonomous vehicles will be improved by using technology that detects road obstacles encountered while driving.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.171-179
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• 2018

In order to ensure the interoperability of products and technologies, companies apply standard technology in R&D but encounter various obstacles in this process, which they try to overcome through active standardization activities. Various studies have investigated the obstacles and coping strategies of companies in the R&D process. However, studies on the obstacles and coping strategies in the standardization process are insufficient, and the types of obstacles related to standardization, so a variety of studies are also needed on the types of activities. In this study, we tried to determine the types of obstacles related to standardization and to examine how these obstacles affect the standardization activities of companies. The analysis used the data from the 'National Standards Survey' which was conducted by the Korean Standards Association in Korea for companies engaged in the electrical, electronic, and information-related fields in Korea. The relationship between standard-related difficulties, needs and standardization activities was verified through structural equation modeling. The analysis results revealed that the standards-related disability issues have some influence on the standardization activities and the mediating effect by the necessity of the standard was investigated. We also found that many companies are making various efforts to overcome the barriers caused by standard activities. This suggests that a company can build a virtuous cycle structure by performing strategic actions to overcome obstacles by standardization activity and reducing the obstacles caused by standard-related research and development.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.64-71
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• 2021

Experimental and analytical investigations are performed to explore the explosion characteristics of a hydrogen-air mixture in open atmosphere. A hydrogen-air mixture tent of total volume of 27 m³, with 40% hydrogen volume, is used to observe overpressure at a distance from the ignition source. Vapor cloud explosion analyses are performed using the TNO multi-energy model and Baker-Strehlow-Tang model. The results of these analyses are compared with experiment done from this study and references. The experimental results with and without obstacles indicate that the overpressure values measured at a distance of 4.5-21.5 m from the ignition source are about 9.4-3.6 kPa and 6.5-2 kPa, respectively. This implies that the overpressure with obstacles is approximately 1.7 times greater than that without obstacles. Analytical observation indicates that the results obtained with the Baker-Strehlow-Tang model with M_f = 0.2-0.35 are in good agreement with those of most of the previous studies, including that obtained from this study. Moreover, the TNO multi-energy model with a volume of 27 m³ well predicts the overpressure obtained from this study. Further studies should considered explosions in semi-confined spaces, which is more suitable for hydrogen refueling stations.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.3-12
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• 2010

In previous studies, the digital measurement systems and analysis algorithms were developed by using the related techniques, such as the aerial photograph detection and high resolution satellite image process. However, these studies were limited in 2-dimensional geo-processing. Therefore, it is necessary to apply the 3-dimensional spatial information and coordinate system for higher accuracy in recognizing and locating of geo-features. The objective of this study was to develop a stochastic algorithm for the optimal sensor placement using the 3-dimensional spatial analysis method. The 3-dimensional information of the LiDAR was applied in the sensor field algorithm based on 2- and/or 3-dimensional gridded points. This study was conducted with three case studies using the optimal sensor placement algorithms; the first case was based on 2-dimensional space without obstacles(2D-non obstacles), the second case was based on 2-dimensional space with obstacles(2D-obstacles), and lastly, the third case was based on 3-dimensional space with obstacles(3D-obstacles). Finally, this study suggested the methodology for the optimal sensor placement - especially, for ground-settled sensors - using the LiDAR data, and it showed the possibility of algorithm application in the information collection using sensors.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.119-125
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• 2008

This paper presents the polygon-based Q-leaning and Cascade Support Vector Machine algorithm for object search with multiple robots. We organized an experimental environment with ten mobile robots, twenty five obstacles, and an object, and then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and Cascade SVM to enhance the fusion model with DBAM and ABAM process.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1132-1138
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• 2012

The MPC (Model Predictive Control) is one of the techniques that can be used to control an unmanned vehicle. It predicts the future vehicle trajectory using the dynamic characteristic of the vehicle and generate the control value to track the reference path. If some obstacles are detected on the reference paths, the MPC can generate control value to avoid the obstacles imposing the inequality constraints on the MPC cost function. In this paper, we propose an obstacle modeling algorithm for MPC with inequality constraints for obstacle avoidance and a method to set selective constraint on the MPC for stable obstacle avoidance. Simulations with the field test data show successful obstacle avoidance and way point tracking performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.2
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• pp.157-165
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• 2016

In wartime conditionsmilitary combat vehicles are required to be driven on rough roads that have significant obstacles. A wheel type dog-horse robot with a rotary suspension system was applied to overcome the obstacles. To achieve real-time analysis, a simplified model was proposed by using velocity transformations. Through comparison with the multi-body dynamics model, the efficiency and accuracy of the proposed modeling was proven.