• 대한조선학회논문집
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• 제60권6호
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• pp.473-481
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• 2023

In this study, a simulation system was developed to verify autonomous navigation algorithm in complex maritime traffic areas. In particular, real-world maritime traffic scenario was applied by considering near real-time maritime traffic information provided by Korean e-Navigation service. For this, a navigation simulation system of Unmanned Surface Vehicle (USV) was integrated with an e-Navigation equipment, called Electronic Chart System (ECS). To verify autonomous navigation algorithm in the simulation system, initial conditions including initial position of an own ship and a set of paths for the ship to follow are assigned by an operator. Then, considering real-world maritime traffic information obtained from the service, the simulation is implemented in which the ship repeatedly travels by avoiding surrounding obstacles (e.g., approaching ships). In this paper, the developed simulation system and its application on verification of the autonomous navigation algorithm in complex maritime traffic areas are introduced.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권1호
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• pp.41-48
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• 2007

Latest advances in network sensor technology and state of the art of mobile robot, and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. In this study, as the preliminary step for developing a multi-purpose "Intelligent Space" platform to implement advanced technologies easily to realize smart services to human. We will give an explanation for the ISpace system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the DIND data fusion with CI of Intelligent Space. We will conclude by discussing some possible future extensions of ISpace. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions tracking multiple objects, human detection and motion assessment, with the results from the simulations run.

• 한국항행학회논문지
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• 제21권3호
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• pp.294-299
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• 2017

홈네트워크 서비스는 가정내의 모든 가전기기가 유무선 네트워크로 연결되어 언제 어디서나 원격교육, 홈오토메이션, 원격 검침, 다양한 엔터테인먼트 등의 컨텐츠를 제공 받을 수 있는 서비스로 진화하고 있다. 본 논문에서는 기존의 홈네트워크의 문제점을 해결하고 사용자에게 보다 효율적으로 쾌적한 홈네트워크 환경을 구성 및 유지하기 위한 방안으로, 외부에서 이동통신 단말기로 댁내 설치된 지능형 홈게이트웨이를 접속하게 되고, 이동통신 단말기 디스플레이 창에는 사용자 접근권한을 확인하기 위해 로그인 페이지가 활성화 되며, 사용자는 자신의 로그인 정보를 통해 인증 절차를 진행하게 된다. 정상적인 인증 절차를 수행하면, 지능형 홈게이트웨이는 사용자와의 네트워크 연결만을 유지하는 기능을 하고, 사용자는 지능형 홈네트워크 시스템으로 접근하게 되는 RFID를 이용한 지능형 홈네트워크 시스템을 제시하였다.

• 한국항행학회논문지
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• 제27권5호
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• pp.635-642
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• 2023

드론은 인공지능 기술의 발달로 단순한 원격 조종 도구를 넘어서 자율적으로 임무를 수행하는 지능형 드론으로 진화하고 있다. 해외 군사 분쟁에서의 드론 활용 사례와, 국내에서 전망한 미래 작전환경 분석에 따라 드론의 중요성이 점차 주목받고 있다. AMAD는 지능형 드론의 신속한 개발을 위해 제안되었다. AMAD를 기반으로 지능형 소프트웨어를 개발하기 위해서는 디버깅, 성능 평가, 모니터링 등의 기능을 사용자에게 지원하는 통합개발환경(IDE)이 필수적이다. 본 논문에서는 지능형 소프트웨어 개발에 필요한 개발환경의 개념들을 정립하여, 이를 IDE 및 IDE와 연동하는 AMAD의 에이전트인 SVI, MPD의 설계에 반영한 결과를 설명한다.

• 로봇학회논문지
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• 제3권3호
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• pp.245-254
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• 2008

Recently, many vision-based navigation methods have been introduced as an intelligent robot application. However, many of these methods mainly focus on finding an image in the database corresponding to a query image. Thus, if the environment changes, for example, objects moving in the environment, a robot is unlikely to find consistent corresponding points with one of the database images. To solve these problems, we propose a novel navigation strategy which uses fast motion estimation and a practical scene recognition scheme preparing the kidnapping problem, which is defined as the problem of re-localizing a mobile robot after it is undergone an unknown motion or visual occlusion. This algorithm is based on motion estimation by a camera to plan the next movement of a robot and an efficient outlier rejection algorithm for scene recognition. Experimental results demonstrate the capability of the vision-based autonomous navigation against dynamic environments.

• 한국항해항만학회지
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• 제28권7호
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• pp.635-640
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• 2004

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

• 제어로봇시스템학회논문지
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• 제10권10호
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• pp.940-946
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• 2004

In this paper, an efficient real-time control architecture for autonomous navigation of powered wheelchair is developed. Since an advanced intelligent wheelchair requires real-time performance, the control software architecture of powered wheelchair is developed under Linux real-time extension Real-time Application Interface (RTAI). A hierarchical control structure for autonomous navigation is designed and implemented using real-time processe and interrupts handling of sensory perception based on slanted surface LRF, emergency handling capability, and motor control with 0.1 msec sampling time. The performance of our powered wheelchair system with the implemented control architecture for autonomous navigation is verified via experiments in a corridor.

• Journal of information and communication convergence engineering
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• 제11권1호
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• pp.24-29
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• 2013

In this paper, we propose a fuzzy inference model for a navigation algorithm for a mobile robot that intelligently searches goal location in unknown dynamic environments. Our model uses sensor fusion based on situational commands using an ultrasonic sensor. Instead of using the "physical sensor fusion" method, which generates the trajectory of a robot based upon the environment model and sensory data, a "command fusion" method is used to govern the robot motions. The navigation strategy is based on a combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance based on a hierarchical behavior-based control architecture. To identify the environments, a command fusion technique is introduced where the sensory data of the ultrasonic sensors and a vision sensor are fused into the identification process. The result of experiment has shown that highlights interesting aspects of the goal seeking, obstacle avoiding, decision making process that arise from navigation interaction.

• 전기학회논문지
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• 제67권12호
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• pp.1648-1656
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• 2018

The configuration of redundant inertial sensors are very important when considering navigation performance and fault detection and isolation (FDI) performance. By constructing a redundant sensor system using multiple inertial sensors, it is possible to improve the navigation performance and fault detection and isolation performance, which are highly related to the sensor configuration and allocation. In order to deploy multiple MEMS inertial measurement units effectively, a configuration and allocation methods considering navigation performance, fault detection and isolation performance, and lever arm effect in one plane are presented, and the performance is analyzed through simulation in this research. From the results, it is confirmed that the proposed configuration and allocation method can improve navigation, FDI, and lever arm effect rejection performances more effectively by more than 70%.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2022년도 추계학술대회
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• pp.170-171
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• 2022

A ship's maneuvering motion model is important in a computer simulation, especially under the trend of intelligent navigation. This model is usually constructed by the hydrodynamic parameters of the ship which are generated by the principles of hydrodynamics. Ship's motion model is a nonlinear function. By using this function, ships' motion elements can be calculated, then the ship's trajectory can be predicted. Deeping neural networks can construct any linear or non-linear equation theoretically if there have enough and sufficient training data. This study constructs some kinds of deep Networks and trains this network by real ship motion data, and chooses the best one of the networks, uses real data to train it, then uses it to predict the ship's trajectory, getting some conclusions and experiences.