• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.135-144
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• 2021

In railway systems, it is common to obtain train location information through an infrastructure-based train detection system. However, this system has a problem that may provide incorrect location information due to non-detection and erroneous detection, which may cause an accident. Therefore, in this study, we propose a method of providing train location information using a sensor-based integrated navigation system. In order to provide accurate information; however, the reliability of the integrated navigation system must be verified. Therefore, in this paper, we develop a simulator that can generate a reference trajectory and sensor data based on the real trajectory and analyze the performance of the integrated navigation system according to various scenarios on the real trajectory.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.3
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• pp.123-130
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• 2015

In this study, a carrier smoothed global positioning system / dead reckoning (CSGPS/DR) integrated system for high-precision trajectory estimation for the purpose of vehicle navigation was proposed. Existing code-based GPS has a low position accuracy, and carrier-phase differential global positioning system (CPDGPS) has a long waiting time for high-precision positioning and has a problem of high cost due to the establishment of infrastructure. To resolve this, the continuity of a trajectory was guaranteed by integrating CSGPS and DR. The results of the experiment indicated that the trajectory precision of the code-based GPS showed an error performance of more than 30cm, while that of the CSGPS/DR integrated system showed an error performance of less than 10cm. Based on this, it was found that the trajectory precision of the proposed CSGPS/DR integrated system is superior to that of the code-based GPS.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.386-395
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• 2016

In trajectory-based navigation systems, a huge amount of trajectory data is needed for efficient route explorations. However, it would be very hard to collect trajectories from all the possible start and destination combinations. To provide a practical solution to this problem, we suggest a method combining collected GPS trajectories data into additional generated trajectories with new start and destination combinations without road information. We present a trajectory combination algorithm and its implementation with Scala programming language on Spark platform for big data processing. The experimental results proved that the proposed method can effectively populate the collected trajectories into valid trajectory paths more than three hundred times.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1636-1645
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• 2016

In navigation systems that use collected trajectory for routing, the number and diversity of trajectory data are crucial despite the infeasible limitation which is that all routes should be collected in person. This paper suggests an algorithm combining trajectories only by collected GPS data and generating new routes for solving this problem. Using distance between two trajectories, the algorithm estimates road intersection, in which it also predicts the correlated direction of them with geographical coordinates and makes a decision to combine them by the correlated direction. With combined and generated trajectory data, this combination way allows trajectory-based navigation to guide more and better routes. In our study, this solution has been introduced. However, the ways in which correlated direction is decided and post-process works have been revised to use the sequential pattern of triangles' area GPS information between two trajectories makes in road intersection and intersection among sets comprised of GPS points. This, as a result, reduces unnecessary combinations resulting redundant outputs and enhances the accuracy of estimating correlated direction than before.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.49-56
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• 2023

As interest in autonomous ships continues to grow, researchers around the world are dedicating themselves to the development of relevant technologies. However, these technologies are not yet perfect. Several technical problems remain unresolved. To address these problems, this study presents the implementation of a ship trajectory algorithm for group navigation, where followers can navigate by following the trajectory of a leader. The algorithm works by storing the leader's trajectory as a follow-point and by calculating the azimuth using the line-of-sight guidance law to reach it. A course-keeping controller based on PD control is implemented to follow the target course and a speed control algorithm is designed to prevent collisions. Sea experiments were conducted using 1 m class small RC model boats to verify the proposed algorithm. The follower successfully navigated by following the leader's trajectory and maintained the designated distance to the forward boat. This study is significant in that it implements an algorithm for the follower to follow the trajectory of the leader rather than directly following it as in conventional methods, and verifies it through sea experiments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.457-462
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• 2005

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is currently one of the most attractive technologies for all. However, unless we find a breakthrough to the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technology. Unlike the industrial robot of the past, today's robots require advanced technologies, such as soft computing, human-friendly interface, interaction technique, speech recognition, object recognition, and many others. In this study, we present a new technological concept named RCP(Robotic Cellular Phone), which combines RT & CP, in the vision of opening a new direction to the advance of CP, IT, and RT all together. RCP consists of 3 sub-modules. They are $RCP^{Mobility}$, $RCP^{Interaction}$, and $RCP^{Interaction}$. $RCP^{Mobility}$ is the main focus of this paper. It is an autonomous navigation system that combines RT mobility with CP. Through $RCP^{Mobility}$, we should be able to provide CP with robotic functionalities such as auto-charging and real-world robotic entertainments. Eventually, CP may become a robotic pet to the human being. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While Trajectory Controller is responsible for the wheel-based navigation of RCP, Self-Localization Controller provides localization information of the moving RCP. With the coordinate information acquired from RFID-based self-localization controller, Trajectory Controller refines RCP's movement to achieve better RCP navigations. In this paper, a prototype system we developed for $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results of the RCP navigation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1701-1704
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• 2005

We developed an machine vision method for navigation control of a traveling automatic guided vehicle(AGV) on desired trajectory with guided marks. The formulated EDF accumulates the edge magnitude for edge directions. The EDF has distinctive peak points at the vicinity of trajectory directions due to the directional and the positional continuities of desired trajectory. Examining the EDF by its shape parameters of the local maxima and symmetry axis results in identifying whether or not change in traveling direction of an AGV has occurred. Simulation results show that the presented method is useful for navigation control of AGV.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.367-374
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• 2018

A trajectory-based scheduling system is proposed for air traffic management using next generation aviation data communication link. Based on the service concept of 4-dimensional trajectory data link (4DTRAD) using air traffic serveices (ATS) datalink Baseline 2, a procedure for trajectory-based operation of an en-route flight is established and described in detail. To mitigate air traffic controllers' workload which might be caused by various and complicated data utilization, a prototype of the scheduling system, which predicts the aircraft trajectory based on the flight intents received by air traffic service system and provides advisory information for air traffic control, was developed. The simulation environment for trajectory based operation was built to validate the scheduling functionality of the prototype.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.