• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.5
• /
• pp.599-604
• /
• 2008

Recently, many researches for autonomous mobile system have been proposed, which can recognize surrounded environment and navigate to destination without outside intervention. The basic sufficient condition for the autonomous mobile system is to navigate to destination safely without accident. In this paper, we propose a path planning method in local region for safe navigation of autonomous system through evaluation of the road surface distortion(damaged/deformed road, unpaved road, obstacle and etc.). We use laser distance sensor to get the information on the road surface distortion and apply image binalization method to evaluate safe region in the detected local region. We show the validity of the proposed method through the computer simulation based on the artificial local road map.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2019.05a
• /
• pp.3-4
• /
• 2019

본 논문에서는 복잡한 해상교통 환경 하에서도 해양 안전을 도모할 수 있는 강화학습 기반 지능형 선박 항해 에이전트 개발의 사전단계로서 기존의 강화학습 환경을 분석하였다. 강화학습 기반 접근법은 선박 항해 에이전트 스스로가 복잡하고 동적인 해상교통 환경을 이해하고 주어진 목표를 달성할 수 있도록 도와주는데, 이를 위해서는 에이전트 자신을 제외한 모든 사항들이 정의되는 환경을 보다 정확하고 효과적으로 개발하는 것이 매우 중요하다. 실제 해상교통 환경은 학습 환경으로의 모델링 및 에이전트 학습의 난이도가 매우 높은 환경으로 학습환경이 가질 수 있는 여러 속성들을 적절히 설정하여 선박 항해 에이전트의 활용 목적에 맞는 가성비 높은 환경을 구축하는 것이 바람직하다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.05a
• /
• pp.200-201
• /
• 2023

Digital twin technology is used in various fields as a method of creating a virtual world to minimize the cost of solving problems in the real world, and is also actively used in the maritime field, such as large-scale systems such as ships and offshore plants. In this paper, we tried to build a digital twin of coastal waters using a ship-handling simulator. The digital twin of the coastal waters developed in this way can be used to safely manage Korea's coastal waters, where maritime traffic is complicated, by providing a actual maritime traffic data. It can be usefully used to develop and advance technologies related to maritime autonomous surface ships and intelligent maritime traffic information services in coastal waters. In addition, it can be used as a 3D-based monitoring equipment for areas where physical monitoring is difficult but real-time maritime traffic monitoring is necessary, and can provide functions to safely manage maritime traffic situations such as aerial views of ports/control areas, bridge views/blind sector views of ships in operation.

• Journal of Internet Computing and Services
• /
• v.21 no.4
• /
• pp.117-126
• /
• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.9
• /
• pp.1202-1208
• /
• 2020

In line with the current era of the 4th Industrial Revolution, it is necessary to prepare for the future by integrating AI elements in the ship sector. In addition, it is necessary to respond to this in the field of power management for the appearance of autonomous ships. In this study, we propose a battery-linked electric propulsion system (BLEPS) algorithm using machine learning's DNN. For the experiment, we learned the pattern of ship power consumption for each operation mode based on the ship data through LabView and derived the battery status through Python to check the flexibility of the generator and battery interlocking. As a result of the experiment, the low load operation of the generator was reduced through charging and discharging of the battery, and economic efficiency and reliability were confirmed by reducing the fuel consumption of 1% of LNG.

• Journal of the Society of Naval Architects of Korea
• /
• v.60 no.3
• /
• pp.155-164
• /
• 2023

About 75% of vessel collision accidents are caused by human error, which causes enormous economic loss, environmental pollution, and human casualties, thus research on automatic collision avoidance of vessels is being actively conducted. In addition, vessels must comply with the COLREGs rules stipulated by IMO when performing collision avoidance with other vessels in motion. In this study, the collision risk was calculated by estimating the position and velocity of other vessels through the Probabilistic Data Association Filter (PDAF) algorithm based on RADAR sensor data. When a collision risk is detected, we propose an event-triggered Nonlinear Model Predict Control (NMPC) algorithm that geometrically creates waypoints that satisfy COLREGs and follows them. To verify the proposed algorithm, simulations through MATLAB are performed.

• Journal of the Society of Naval Architects of Korea
• /
• v.60 no.4
• /
• pp.248-255
• /
• 2023

In order to implement the autonomous navigation function, it is essential to track an object within a certain radius of the ship's route. This paper proposes the Multiple Probabilistic Data Association Filter (MPDAF), which can track multiple ships by extending Probabilistic Data Association Filter (PDAF), an existing single object tracking algorithm, using radar data obtained from real marine environments. The proposed MPDAF algorithm was developed to address the problem of tracking multiple objects in a complex environment where there can be significant uncertainty in the number and identification of objects to be tracked. Using real-world radar data provided by the German aerospace center (DLR), it has been verified that the proposed algorithm can track a large number of objects with a small position error.

• Journal of the Society of Naval Architects of Korea
• /
• v.45 no.5
• /
• pp.554-561
• /
• 2008

This paper deals with an intelligent digital ship which aims at development to support economic and safe services through an integration into the hierarchically layered digital signals such as ship's navigation, maneuvering and control signal and establishing a one-man bridge system in order to provide a support systems between ship and land station. This paper introduces the results of the mid-term project sponsored from Ministry of Commerce, Industry and Energy which consists of three sub-project such as INS(Intelligent Navigation System), AIS(Automatic Identification System), and IMIT (Integrated Maritime Information Technology). The INS system that can allow ships to navigate economically and safely through the integration and analysis of national data within the ship. AIS is a system that reports automatically on the location of the ship in order to prevent the collision between ships and between the ship and the land. IMIT is a integrated system for providing an efficient and economic support system between ships and the land and a ship-land platform and technologies.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.2
• /
• pp.151-158
• /
• 2019

Wireless communication technology (WAVE) for vehicles, which is the core technology behind the next-generation intelligent transport system (C-ITS), is used to deliver information about vehicles to prevent traffic accidents and traffic situations that may arise between vehicles and infrastructure. Similar traffic issues often arise in marine scenarios. Currently, AIS is being used as a means of transmitting information such as the status of relative vessels, but research is being carried out to solve problems with AIS such as overloading by applying wireless communication technology for vehicles to the sea. In this study, a collision warning system suitable for small-sized vessels was developed based on the marine application of WAVE for vehicles verified through prior research, and the adequacy of this collision warning system was reviewed through a practical test. It is expected that this system will contribute greatly to future e-Navigation applications or self-driving ships as well as to preventing marine accidents.

• Journal of Navigation and Port Research
• /
• v.41 no.6
• /
• pp.381-388
• /
• 2017

Recently, renewed attention for technological applications within the maritime industry has taken place, particularly regarding unmanned vessels. There has been a lot of interest about the number of projects aiming at testing the operational feasibility of unmanned vessels, particularly in relation to technological, safety and security issues. Nevertheless, no studies have investigated this issue from the point of view of seafarers towards unmanned vessels; this paper aims at filling this gap. Data has been collected through a survey questionnaire. A Pearson correlational coefficient has been used to test the correlation between some of the variables. The results show that more than half of the respondents indicated that unmanned vessels do not contribute to an increase in accidents at sea. In addition, seafarers believe unmanned vessels will not be operational in the near future, with most of the respondents indicating a 10-20 year time frame. Thirdly, most of the respondents(both officers and ratings).