• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.92.2-92
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• 2002

Building autonomous robots have been a central objective of research in artificial intelligence. The development of techniques for autonomous navigation in real environment consist one of the main tendencies of the current researches about Robotics. An important problem in autonomous navigation is the necessity of dealing with a great amount of uncertainties inherent to the real environments. The paraconsistent logic has characteristics that make it become an adequate tool to solve this problem. In this work, it is proposed a technique of mapping the real world in the navigation of an autonomous robot using the paraconsistent logic.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.3-4
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• 2021

Korea government has developed Korean e-Navigation service to assist ship's collision avoidance, and is providing it since Jan. 2021 to korean vessels to reduce marine accidents caused by human error which is regarded as main reason of marine accidents. It is a huge achievement itself because it is a real-time maritime safety information service based on digital communication, but still has room for improvement to provide customized information for each vessel, such as considering ship's characteristics. This research analyzes current status and requirement of collision avoidance assistance service. Lastly, it suggests direction of improvement of service such as using data science, artificial intelligence(AI).

• Journal of Gastric Cancer
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• v.23 no.3
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• pp.400-409
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• 2023

Artificial intelligence (AI) has made significant progress in recent years, and many medical fields are attempting to introduce AI technology into clinical practice. Currently, much research is being conducted to evaluate that AI can be incorporated into surgical procedures to make them safer and more efficient, subsequently to obtain better outcomes for patients. In this paper, we review basic AI research regarding surgery and discuss the potential for implementing AI technology in gastric cancer surgery. At present, research and development is focused on AI technologies that assist the surgeon's understandings and judgment during surgery, such as anatomical navigation. AI systems are also being developed to recognize in which the surgical phase is ongoing. Such a surgical phase recognition systems is considered for effective storage of surgical videos and education, in the future, for use in systems to objectively evaluate the skill of surgeons. At this time, it is not considered practical to let AI make intraoperative decisions or move forceps automatically from an ethical standpoint, too. At present, AI research on surgery has various limitations, and it is desirable to develop practical systems that will truly benefit clinical practice in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.47-49
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• 2022

Robot navigation has seen a major improvement since the the rediscovery of the potential of Artificial Intelligence (AI) and the attention it has garnered in research circles. A notable achievement in the area was Deep Learning (DL) application in computer vision with outstanding daily life applications such as face-recognition, object detection, and more. However, robotics in general still depend on human inputs in certain areas such as localization, navigation, etc. In this paper, we propose a study case of robot navigation based on deep reinforcement technology. We look into the benefits of switching from traditional ROS-based navigation algorithms towards machine learning approaches and methods. We describe the state-of-the-art technology by introducing the concepts of Reinforcement Learning (RL), Deep Learning (DL) and DRL before before focusing on visual navigation based on DRL. The case study preludes further real life deployment in which mobile navigational agent learns to navigate unbeknownst areas.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.388-389
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• 2022

Recently, AI (Artificial Intelligence) has been applied to various technologies such as automatic driving, robot and smart communication. Currently, AI system is developed by software-based method using tensor flow, and GPU (Graphic Processing Unit) is employed for processing unit. However, if software-based method employing GPU is used for AI applications, there is a problem that we can not change the internal circuit of processing unit. In this method, if high-level jobs are required for AI system, we need high-performance GPU, therefore, we have to change GPU or graphic card to perform the jobs. In this work, we developed a CNN-based FPGA (Field Programmable Gate Array) chip to solve this problem.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.566-573
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• 2024

Applying autonomous driving technology to construction sites is very difficult due to safety issues. However, the application of various positioning and sensing devices, such as cameras and radars, to construction equipment is very active. Based on these technological trends, the government is making various efforts, including the Serious Accident Punishment Act and support for industrial safety management expenses, to reduce the incidence of accidents caused by construction equipment and industrial vehicles. And, related industries have been developing various safety equipment over the past few years and applying them to the field. In this paper, we investigate the current status of safety equipment-related technologies currently applied to construction equipment and industrial vehicles, and propose a direction for the development of safety technology in construction equipment based on artificial intelligence. Improving the safety and work efficiency of construction equipment based on the technology proposed in this paper should be reviewed through simulation in the future.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.466-471
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• 2024

Recently, the Machine Learning based Artificial Intelligence has introduced in aviation field. In most cases, safety assurance of aviation software is achieved by applying RTCA DO-178C or DO-278A or similar standards. These standards were developed for and are well-suited to software that has inherent deterministic properties and explainability. Considering the characteristics of AI software based on ML, it is not feasible to assure the integrity of those new aviation systems using traditional software assurance standards mentioned above. In this paper, we research the certification framework that is newly suggested by EASA to deal with the aviation system including ML AI functions, and discuss what should the Korean authority and related industries prepare to cope with this issue.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.445-446
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• 2022

In this paper, in order to improve port work preparation and berth scheduling efficiency in an artificial intelligence-based berthing monitoring system that can monitor the ship's berthing process, we develop a mooring line recognition model to check an exact berthing time. By improving the pre-designed AI model, it is possible to segment the mooring line from the input image, and to recognize when the mooring line arrives or falls on the berth, thereby providing the correct ship's berthing time. The proposed AI model confirmed by the results that mooring line recognition is possible with evaluation data about the actual berthing situation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.147-148
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• 2022

Recently, as a number of accidents occur while berthing ships, the need for safety measures for ship operation in ports is emphasized. In order to quantitatively analyze the contents of safety measures in Busan New Port, this study collected ship trajectory data,, and based on this data, applied a maritime artificial intelligence algorithm to analyze the trajectory pattern. As a result, the waypoint of the ship arriving and departing Busan New Port was derived and the operation pattern of the ship's speed and course was proposed.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.23-30
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• 2024

This paper studies a GPS error filtering method that takes into account the continuity of the ongoing path to enhance the safety of autonomous agricultural mobile robots. Real-Time Kinematic Global Positioning System (RTK-GPS) is increasingly utilized for robot position evaluation in outdoor environments due to its significantly higher reliability compared to conventional GPS systems. However, in orchard environments, the robot's current position obtained from RTK-GPS information can become unstable due to unknown disturbances like orchard canopies. This problem can potentially lead to navigation errors and path deviations during the robot's movement. These issues can be resolved by filtering out GPS information that deviates from the continuity of the waypoints traversed, based on the robot's assessment of its current path. The contributions of this paper is as follows. 1) The method based on the previous waypoints of the traveled path to determine the current position and trajectory. 2) GPS filtering method based on deviations from the determined path. 3) Finally, verification of the navigation errors between the method applying the error filter and the method not applying the error filter.