• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.196-202
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• 2024

The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2760-2769
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• 2011

An intelligent autonomous robot generates a plan to achieve a goal. A plan is a sequence of robot actions that accomplish a given mission by being successfully executed. However, in the complex and dynamic real world, a robot may encounter unexpected situations and may not execute its planned actions any more. Therefore, an intelligent autonomous robot must prepare an efficient handling process to cope with these situations to successfully complete a given mission. Plan repair with milestone states is an efficient method to cope with the situation. It retains the advantages of other plan repair procedures. This paper proposes a regressive method of formulating milestone states and a method of assigning weighting values on conditions that compose a milestone state. The task to repair a plan may employ the weighting values as its job priority. The regressive method formulates less complex milestone states and leads to the conditions of a milestone state to take pertinent weighting values for an efficient handling procedure to repair a plan with milestone states.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.477-482
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• 1994

As the need for switchover to FA and for rationalization increases in the industrial world, educational courses in schools are more and more taking up the subjects of electronic machines, mechatronics and systems, etc., subjects which are a fusion of the previous subjects of electricity, electronics and machines. At our junior college, a control engineering course was inaugurated in 1974 prior to any other schools that offered such courses. As automation progressed, the use of industrial robots spread rapidly. The year of 1980 is regarded as the first year that the use of industrial robots become widespread. Responding to the current requests, a one-year research course was added to the control engineering course in 1983. Moreover, a robot engineering course was newly established in 1984, in which mechatronics and industrial robotics were instructed intensively in high efficiency. As a teaching aid, an air robot system which was based particularly on the FMS model and possessed pattern recognition capabilities was completed in 1982. This system has been used since then as the nucleus for hands-on training with robots and systems. As more and more intelligent machines and artificial intelligence become widespread in industry, these subjects are taking on greater importance and greater sophistication in the education offered by this department. Educational institutions are seeking to provide facilities and curricula which will meet the technological needs of this age. Our college is not an institution at the graduate school level, but rather a school which is at the more practical junior college level. An outline of the facilities introduced at our school is presented and the results of utilizing it in industrial robot engineering education is reported.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.720-725
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• 2004

Robot systems have applied to manufacturing or industrial field for reducing the need for human presence in dangerous and/or repetitive tasks. However, robot applications are transformed from industrial field to human life in recent tendency Nowadays, final goal of robot is to make a intelligent robot that can understand what human say and learn by itself and have internal emotion. For example Home service robots are able to provice functions such as security, housework, entertainment, education and secretary To provide various functions, home robots need to recognize human`s requirement and environment, and it is indispensable to use artificial intelligence technology for implementation of home robots. In this paper, implemented robot system takes data from several sensors and fuses the data to recognize environment information. Also, it can select a proper behavior for environment using soft computing method. Each behavior is composed with intuitive motion and sound in order to let human realize robot behavior well.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.313-327
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• 2018

In this era that technology is replacing human labor is coming. Like the introduction of Factory Automation and Smart Factory to enhance the productivity in manufacturing works in companies, RPA (Robotic Process Automation) is being applied to strengthen the competiveness in service & office work of companies. But, RPA itself is not mature enough to be the specific technology or solution, but burgeoning as the conceptual technology alternatives to automate the business process harnessed with the concept of software robots, artificial intelligence etc. The biggest difference that the introduction of RPA can make is the transition of the work based on 'human labor', to the 'digital labor' that could result in the replacement of human labor itself with that. Considering this kind of impact to change the concept of labor, the discussion for the future policy for this is inevitable. In this paper, beginning from the overview of RPA, relevant concerns & consideration for the application of RPA will be described based on the understanding of industrial & technology trends and expected future of RPA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1013-1018
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• 2021

Due to the recent accident caused by the automated vehicle, discussions on the ethical aspects of AI have been actively underway. This paper confirms that AI is inevitably connected to ethical components through the concepts and techniques related to robots-AI, and argues that ethical aspects are built-in, not post facto. Furthermore, this devises a solution to the trolley dilemma that can serve as a clue to ethical problems associated with automated vehicles. Preferentially, that process contains writing Bayesian networks. Next, only important and influential data are left after the pre-processing stage, and crowd-sourcing & extrapolation is used to calculate the exact figures of the networks. Through this process, this argues that humans' subjects are certainly included in implementing algorithms and models and discusses the necessity and direction of engineering liberal arts, especially education of ethics that distinguished from major education to prevent distortions and biases abouts AI systems.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.17-22
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• 2024

Recently, as the ICT field has been used in various environments, it has become possible to analyze pests by crops, use robots when harvesting crops, and predict by big data by utilizing ICT technologies in a sustainable agricultural environment. However, in a sustainable agricultural environment, efforts to solve resource depletion, agricultural population decline, poverty increase, and environmental destruction are constantly being demanded. This paper proposes an artificial intelligence-based big data processing analysis method to reduce the production cost and increase the efficiency of crops based on a sustainable agricultural environment. The proposed technique strengthens the security and reliability of data by processing big data of crops combined with AI, and enables better decision-making and business value extraction. It can lead to innovative changes in various industries and fields and promote the development of data-oriented business models. During the experiment, the proposed technique gave an accurate answer to only a small amount of data, and at a farm site where it is difficult to tag the correct answer one by one, the performance similar to that of learning with a large amount of correct answer data (with an error rate within 0.05) was found.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.370-376
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• 2022

Smart ships related studies are being conducted in various fields owing to the development of technology, and an engine room patrol robot that can patrol the unmanned engine room is one such study. A patrol robot moves around the engine room based on the information learned through artificial intelligence and checks the machine normality and occurrence of abnormalities such as water leakage, oil leakage, and fire. Study on engine room patrol robots is mainly conducted on machine detection using artificial intelligence, however study on movement and control is insufficient. This causes a problem in that even if a patrol robot detects an object, there is no way to move to the detected object. To secure maneuverability to quickly identify the presence of abnormality in the engine room, this study experimented with whether a patrol robot can determine the shortest path by applying the A* algorithm. Data were obtained by driving a small car equipped with LiDAR in the ship engine room and creating a map by mapping the obtained data with SLAM(Simultaneous Localization And Mapping). The starting point and arrival point of the patrol robot were set on the map, and the A* algorithm was applied to determine whether the shortest path from the starting point to the arrival point was found. Simulation confirmed that the shortest route was well searched while avoiding obstacles from the starting point to the arrival point on the map. Applying this to the engine room patrol robot is believed to help improve ship safety.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.8
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• pp.359-368
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• 2017

What is the term "intelligence information society", which is a term that has been continuously discussed recently? This means that the automation beyond the limits of human ability in the whole societies based on intelligent information technology is a universalized social future. In particular, it is a concept that minimizes human intervention and continuously pursues evolution to data (or big data) -based automation. For example, autonomous automation is constantly aiming at unmanned vehicles with artificial intelligence as a key element. However, until now, intelligent information research has focused on the intelligence itself and has made an effort to improve intelligence logic and replace human brain and intelligence. On the other hand, in order to replace the human labor force, we have continued to make efforts to replace workers with robots by analyzing the working principles of workers and developing optimized simple logic. This study proposes important strategies and directions to implement intelligent information education policy and intelligent information technology research strategy by suggesting access strategy, education method and detailed policy road map for intelligent information technology research strategy and educational service. In particular, we propose a phased approach to intelligent information education such as basic intelligence education, intelligent content education, and intelligent application education. In addition, we propose education policy plan for the improvement of intelligent information technology, intelligent education contents, and intelligent education system as an important factor for success and failure of the 4th industrial revolution, which is centered on intelligence and automation.