• Aerospace Engineering and Technology
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• v.4 no.2
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• pp.88-93
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• 2005

A conceptual study about the angle information based orbit determination technique for a geostationary satellite was performed. With an assumption that the simultaneous observing of the earth and nearby stars is possible, we confirmed that the view angles between the earth and stars can be use as inputs for orbit determination process. By the MATLAB simulation with least square method, the convergence is confirmed. This conceptual study was performed with the COMS for instance. This technique will be able to use as a back-up of ground station's orbit determination or a part of autonomous satellite operation.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.158-163
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• 2012

Spherical Flying Machine, unlike conventional aircraft structure, is protected by circular frame. This battery-operated propeller machine, which can do vertical take-off and hovering, is under development for indoor and outdoor operation and dubbed as Flying Ball in KARI. In the future, autonomous air vehicle will be constructed for reconnaissance and surveillance application.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.233-242
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• 2009

This paper briefly reviews the path planning methods that are applicable to the autonomous mobile robots for the military. Two distinct path search algorithms, $A^*$ and $D^*$ that are most popular and flexible in public applications, among those reviewed are coded and analyzed in terms of combat environment assessment factors called METT+TC for the area of operations. The results imply that it is important to consider the characteristics of defense acquisition process and the specific requirements of defense operation so that the successful technology development of the Robot products is directly linked to the defense procurement of Robot products.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.127-138
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• 2005

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1072-1079
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• 2014

This paper introduces a coordinated droop control for the stand-alone DC micro-grid, which is composed of photo-voltaic generator, wind power generator, engine generator, and battery storage with SOC (state of charge) management system. The operation of stand-alone DC micro-grid with the coordinated droop control was analyzed with computer simulation. Based on simulation results, a hardware simulator was built and tested to analyze the performance of proposed system. The developed simulation model and hardware simulator can be utilized to design the actual stand-alone DC micro-grid and to analyze its performance. The coordinated droop control can improve the reliability and efficiency of the stand-alone DC micro-grid.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.110-117
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• 2022

This paper describes a localization algorithm utilizing relative observations for multiple autonomous underwater vehicles (Multiple-AUVs). In order to maximize the efficiency of operation and mission accomplishment and to prevent problems such as collision and interference, the locations and directions of Multiple-AUVs must be precisely estimated. To estimate the locations and directions, we designed a localization algorithm utilizing relative observations and verified it with simulations based on sensor data sets acquired through real sea experiments. Also, an optimal combination of relative observation information for efficient localization is figured out through combining various relative observations. The proposed method shows improved localization results compared to those only using the navigation algorithm. The performance of localization is improved up to 58% depending on the combination of relative observations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.597-606
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• 2020

Because the USV(Unmanned Surface Vehicle) is capable of remote control or autonomous navigation at sea, it can secure the superiority of combat power while minimizing human losses in a future combat environment. To plan the technology for the development of USV, the trend analysis of related technology and the selection of promising technology should be preceded, but there has been little research in this area. The purpose of this paper was to measure and evaluate the technology trends quantitatively. For this purpose, this study analyzed the technology trends and selected promising/declining technologies using topic modeling of papers and patent data. As a result of topic modeling, promising technologies include control and navigation, verification/validation, autonomous level, mission module, and application technology, and declining technologies include underwater communication and image processing technology. This study also identified new technology areas that were not included in the existing technology classification, e.g., technology related to research and development of USV, artificial intelligence, launch/recovery, and operation, such as cooperation with manned and unmanned systems. The technology trends and new technology areas identified through this study may be used to derive key technologies related to the development of the USV and establish appropriate R&D policies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.208-215
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• 1995

Numerous solution methods for scheduling problems such as part dispatching problem, operation sequence problem have been suggested as a means to be embedded in hierarchical or centralized shop floor control. Under the preceding control philosophies, however, response to changes in the shop floor status is quite slow and timely decision is sometimes impossible. Moreover, the control software becomes too large and it is almost impossible to modify the control software when the configuration of the shop floor changes. In agile manufacturing which emerged recently to cope with quick response and easy modifiability when unexpected changes occur, a new control policy is needed. CSCW[Computer Supported Cooperative Work] based shop floor control casts a different view on scheduling problems. Decisions are made locally when requested and useful information is scattered among agents for its efficient use. Adaptation is easy because agents are -'plug compatible or portable. In this paper, scheduling problems occurring under CSCW based shop floor control are identified and characterized. Traditional scheduling problems are reviewed from the CSCW viewpoint. All the control entities involved in the shop floor can be found and used to defined agents. With these entities and CSCW concept, possible scheduling problems are identified.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1669-1676
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• 2020

The IAEA held the IAEA Robotics Challenge 2017 (IRC2017) to protect workers during inspections of spent nuclear fuel and to improve work efficiency and accuracy rates. To this end, we developed an unmanned surface vehicle (USV) system called the spent fuel check vehicle (SCV). The SCV extracts and tracks the target through image processing, and it is necessary to find suitable parameters for the SNF storage environment in advance. This preliminary work takes time. It is also difficult to prepare the environment in which the work will proceed. In addition, if the preliminary work does not proceed as planned, the system will not move at the proper speed and will become unstable, with yawing and overshoot. To solve this problem, we developed a controller with a camera that can extract the depth at which the target is stored and allow distance-adaptive control. This controller is able to attenuate system instability factors such as yawing and overshoot better than existing controllers by continuously changing system operation parameters according to the depth. In addition, the time required for preliminary work during inspections can be shortened.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.384-394
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• 2020

This paper proposes an outlier detection model based on machine learning that can diagnose the presence or absence of major engine parts through unsupervised learning analysis of main engine big data of a ship. Engine big data of the ship was collected for more than seven months, and expert knowledge and correlation analysis were performed to select features that are closely related to the operation of the main engine. For unsupervised learning analysis, ensemble model wherein many predictive models are strategically combined to increase the model performance, is used for anomaly detection. As a result, the proposed model successfully detected the anomalous engine status from the normal status. To validate our approach, clustering analysis was conducted to find out the different patterns of anomalies the anomalous point. By examining distribution of each cluster, we could successfully find the patterns of anomalies.