• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.139-146
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• 2011

This paper presents a new modified Contract Net Protocol (CNP) for microgrid operation based on multiagent system. The CNP is a widely used protocol for interactions among distributed problem solving. The Contract Net Interaction Protocol of the Foundation for Intelligent Physical Agents (FIPA-CNIP) is a minor modification of the original CNP for multiagent system applications. In this paper, a modified CNP (MCNP) based on the FIPA-CNIP is proposed for more specialized interactions among agents for microgrid operation. A multiagent system is designed and constructed for microgrid operation. A microgrid operation based on the multiagent system is tested to check the functionality of the proposed MCNP.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.246-254
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• 2010

This paper presents a multiagent system for microgrid operation in the grid-interconnected mode. An energy market environment with generation competition is adopted for microgrid operation in order to guarantee autonomous participation and meet the requirements of participants in the microgrid. The modified Contract Net Protocol (CNP) is used as a protocol for interactions among agents. The multiagent system for microgrid operation based on the modified CNP and the energy market environment is designed and implemented. To verify the feasibility of the suggested multiagent system, experiments on three operation conditions are carried out.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.296-301
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• 2019

Artificial intelligence is closely linked to our real lives, leading innovation in various fields. Especially, as a means of transportation possessing artificial intelligence, autonomous unmanned vehicles are actively researched and are expected to be put into practical use soon. Autonomous cars and autonomous unmanned aerial vehicles are required to equip accurate navigation system so that they can find out their present position and move to their destination. At present, the navigation of transportation that we operate is mostly dependent on GPS. However, GPS is vulnerable to external intereference. In fact, since 2010, North Korea has jammed GPS several times, causing serious disruptions to mobile communications and aircraft operations. Therefore, in order to ensure safety in the operation of the autonomous unmanned vehicles and to prevent serious accidents caused by the intereference, rapid situation judgment and countermeasure are required. In this paper, based on big data and machine learning technology, we propose a countermeasure system for GPS interference that supports decision making by applying John Boyd's OODA loop cycle (detection - direction setting - determination - action).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.611-616
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• 2018

With the recent increase in awareness of the diversification of patterns of warfare and security, technological evolution is occurring in the field of autonomous defense robots. As defense science and technology develops with the development of the concept of military utilization focusing on human lives and economic operation, the importance of autonomous robots in the effect-oriented future battlefield is increasing. The major developed countries have developed core technologies, investment strategies, priorities, data securing strategies and infrastructure development related to the field of autonomous defense robots, and research activities such as technology planning and policy strategy for autonomous defense robots in Korea have already begun. In addition, the field of autonomous defense robots encompasses technologies that represent the fourth industrial revolution, such as artificial intelligence, big data, and virtual reality, and so the expectations for this future area of technology are very high. It is difficult to predict the path of technological development due to the increase in the demand for new rather than existing technology. Moreover, the selection and concentration of strategic R&D is required due to resource constraints. It is thought that a preemptive response is needed. This study attempts to derive 6 new technologies that will shape the future of autonomous defense robots and to obtain meaningful results through an empirical study.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.315-324
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• 2017

The smart grid with distributed power supply introduces a number of problems including not only the problems of the existing power grid but also the problem of protection co-operation due to new electric phenomenon because it has a mixed operation structure combining the existing radial operation structure and the new loop operation structure. The EMTP based power system analysis method has flexibility and convenience from the view of system configuration but it requires another experimental verification because of uncertainty of design and analysis results. On the other hand, the real demonstration system has difficulties in observing accurate fault on large scale system due to considerable economical and spatial construction cost, system configuration constraint, and it is difficult to demonstrate the distributed, autonomous and adaptive control strategy of smart grid. In this paper, a basic theory for a micro smart grid simulator design using MEMS(Micro Electro-Mechanical Systems) miniaturization technology is studied which can safely and freely experiment and observe electrical phenomena, and distribution, autonomous adaptive control strategy for disturbances on 22.9kV smart grid under minimum economic and spatial cost.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.182-189
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• 2023

Depth estimation is a key technology in 3D map generation for autonomous driving of vehicles, robots, and drones. The existing sensor-based method has high accuracy but is expensive and has low resolution, while the camera-based method is more affordable with higher resolution. In this study, we propose self-attention-based unsupervised monocular depth estimation for UAV camera system. Self-Attention operation is applied to the network to improve the global feature extraction performance. In addition, we reduce the weight size of the self-attention operation for a low computational amount. The estimated depth and camera pose are transformed into point cloud. The point cloud is mapped into 3D map using the occupancy grid of Octree structure. The proposed network is evaluated using synthesized images and depth sequences from the Mid-Air dataset. Our network demonstrates a 7.69% reduction in error compared to prior studies.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.33-46
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• 2023

The Autonomous ships are equipped with a function to judge and navigate the sea conditions on their own, so the job of the ship officer who operates it changes. The educational curriculum to nurture ship officer with the ability to operate and manage autonomous ships must also be changed. This study aimed to develop the curriculum for training autonomous ship officer by using the Delphi survey method suitable for predicting the uncertain future. Among the current 61 subjects for training ship officer identified in the Delphi survey, 32 subjects with high importance should be maintained in the training for autonomous ship officer, and subjects with low importance should be abolished or integrated into other subjects. These subjects were collectively referred to as 'general courses'. The expert panel of the Delphi survey suggested 42 items as new subjects, with 18 items of 'high', 14 items of 'middle', and 10 items of 'low'. Through in-depth analysis of these items by experts, 27 subjects were adjusted and three courses were proposed : 1)'Basic course(10 courses)' for developing basic capabilities such as basic theories for understanding advanced technology and information applied to autonomous ships, 2)'Job course(10 courses)' for practical competency directly related to autonomous ship operation, 3)'Intensive course(7 subjects)' for fostering land remote operators of autonomous ships. Since the introduction and spread of autonomous ships will progress rapidly, research to develop and supplement autonomous ship pilot training courses should be continued by reflecting the level of autonomous navigation of autonomous ships.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.163-170
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• 2023

As the development of the 4th industrial revolution in the maritime industry has accelerated, the technical development and progress of maritime autonomous surface ship(MASS), and the development of international regulations have been accelerated. In particular, the IMO Maritime Safety Committee(MSC) has established a road-map for the development of the non-mandatory goal-based MASS instrument(MASS Code) and started developing a non-mandatory MASS Code at MSC 105th meeting. Many countries are actively participating in the Correspondence Group on the development of MASS Code, and the development of detailed requirements for MASS functions in the MASS Code is underway. Especially, the concept of "Mode of Operation" for MASS functions was mentioned in the Correspondence Group for the first time, and it is expected that discussions on these modes will be conducted from the IMO MASS JWG meeting to held in April 2023. The concept of "Mode of Operation" will be useful in explaining MASS and MASS functions and will be discussed continually for the development of MASS Code. This paper reviews the contents of the IMCA M 220 document, which provides guidelines on operating modes, to conduct research on the benchmark for setting the operating modes of MASS.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1307-1312
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• 2023

In this paper, we propose a hybrid camera system that combines cameras with different focal lengths and LiDAR (Light Detection and Ranging) sensors to address the core components of autonomous driving perception technology, which include object recognition and distance measurement. We extract objects within the scene and generate precise location and distance information for these objects using the proposed hybrid camera system. Initially, we employ the YOLO7 algorithm, widely utilized in the field of autonomous driving due to its advantages of fast computation, high accuracy, and real-time processing, for object recognition within the scene. Subsequently, we use multi-focal cameras to create depth maps to generate object positions and distance information. To enhance distance accuracy, we integrate the 3D distance information obtained from LiDAR sensors with the generated depth maps. In this paper, we introduce not only an autonomous vehicle platform capable of more accurately perceiving its surroundings during operation based on the proposed hybrid camera system, but also provide precise 3D spatial location and distance information. We anticipate that this will improve the safety and efficiency of autonomous vehicles.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.89-94
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• 2002

In this paper, a protection system using a Multi-Agent concept for power distribution networks is proposed. Every digital over current relay(OCR) is developed as an agent by adding its own intelligence, self-tuning and communication ability. The main advantage of the Multi-Agent concept is that a group of agents work together to achieve a global goal which is beyond the ability of each individual agent. In order to cope with frequent changes in the network operation condition and faults, an OCR agent, suggested in this paper, is able to detect a fault or a change in the network and find its optimal parameters for protection in an autonomous manner considering information of the whole network obtained by communication between other agents. Through this kind of coordination and information exchanges, not only a local but also a global protective scheme is completed. Simulations in a simple distribution network show the effectiveness of the suggested protection system.