• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.701-704
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• 2010

In studying an autonomous navigation technique of UUV(Unmaned Underwater Vehicle), one of the many fundamental techniques is to plan a 3D path to complete the mission via realtime information received by sonar showing landscapes and obstacles. The simulation system is necessary to verify the algorithm in researching and developing 3D path planning of UUV. It is because 3D path planning of UUV should consider guide control, the dynamics, ocean environment, and search sonar models on the basis of obstacle avoidance technique. The simulation system developed in this paper visualizes the UUV's movement of avoiding obstacles, arriving at the goal position via waypoints by using C++ and OpenGL. Plus, it enables the user to setup the various underwater environment and obstacles by a user interface. It also provides a generalization that can verify path planning algorithm of UUV studied in any developing environment.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.3
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• pp.170-184
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• 2024

With the advancement of autonomous navigation technology in maritime domain, there is an active research on swarming Unmanned Surface Vehicles (USVs) that can fulfill missions with low cost and high efficiency. In this study, we propose a formation control algorithm that maintains a certain shape when multiple unmanned surface vehicles operate in a swarm. In the case of swarming, individual USVs need to be able to accurately follow the target state and avoid collisions with obstacles or other vessels in the swarm. In order to generate guidance commands for swarm formation control, the potential field method has been a major focus of swarm control research, but the method using the potential field only uses the position information of obstacles or other ships, so it cannot effectively respond to moving targets and obstacles. In situations such as the formation change of a swarm of ships, the formation control is performed in a dense environment, so the position and velocity information of the target and nearby obstacles must be considered to effectively change the formation. In order to overcome these limitations, this paper applies a method that considers relative velocity to the potential field-based guidance law to improve target following and collision avoidance performance. Considering the relative velocity of the moving target, the potential field for nearby obstacles is newly defined by utilizing the concept of Velocity Obstacle (VO), and the effectiveness and efficiency of the proposed method is verified through swarm control simulation, and swarm control experiments using a small scaled unmanned surface vehicle platform.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.400-407
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• 2024

The role of unmanned aerial vehicles (UAVs) in modern warfare is increasingly significant, making their capacity for autonomous missions essential. Accordingly, autonomous target detection/identification based on captured images is crucial, yet the effectiveness of AI models depends on image sharpness. Therefore, this study describes how to determine the field of view (FOV) of the camera and the flight position of the UAV considering the required spatial resolution. Firstly, the calculation of the size of the acquisition area is discussed in relation to the relative position of the UAV and the FOV of the camera. Through this, this paper first calculates the area that can satisfy the spatial resolution and then calculates the relative position of the UAV and the FOV of the camera that can satisfy it. Furthermore, this paper propose a method for calculating the effective range of the UAV's position that can satisfy the required spatial resolution, centred on the coordinate to be photographed. This is then processed into a tabular format, which can be used for mission planning.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.3-20
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• 2022

Recently, prior to the commercialization of urban air mobility (UAM), the importance of R&D for air transportation-related industries in urban areas has significantly increased. To create a UAM environment, research is being conducted on personal air vehicles (PAVs). They are key means of air transportation, but research on the physical factors influencing their passengers is relatively insufficient. In particular, because the PAV is expected to be used as a living space for the passengers, research on the effects of the physical elements generated in the PAV on the human body is essential to design an interior space that supports the in-vehicle activities of the passengers. Therefore, the purpose of this study is to derive the constraint factors that affect the human body due to the air navigation characteristics of the PAV and to understand the impact of these constraint factors on the bodies of the passengers performing in-vehicle activities. The results of this study indicate that when the PAV was operated at less than 4,000 ft, which is the operating standard, the constraint factors were noise, vibration, and motion sickness caused by low-frequency motion. These constraint factors affect in-vehicle activity; thus, the in-vehicle activities that can be performed in a PAV were derived using autonomous cars, airplanes, and PAV concept cases. Furthermore, considering the impact of the constraint factors and their levels on the human body, recommended constraint factor criteria to support in-vehicle activities were established. To reduce the level of impact of the constraint factors on the human body and to support in-vehicle activity, the seat's shape and built-in functions of the seat (vibration reduction function, temperature control, LED lighting, etc.) and external noise reduction using a directional speaker for each individual seat were recommended. Moreover, it was suggested that interior materials for noise and vibration reduction should be used in the design of the interior space. The contributions of this study are the determination of the constraint factors affecting the in-vehicle PAV activity and the confirmation of the level of impact of the factors on the human body; in the future, these findings can be used as basic data for suitable PAV interior design.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.145-150
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• 2016

The capability of accurate positioning and tracking is necessary to implement an unmanned autonomous driving system. The moving-baseline GPS Technique is a promising candidate to mitigate positioning errors of conventional GPS system. It provides accurate positioning data based on the phase difference between received signals from multiple GPS antennas mounted on the same platform. In this paper, we propose a dual-band dual-circularly-polarized antenna suitable for the moving-baseline GPS. The proposed antenna operates at GPS L1 and L2 bands, and fed by the side of the antenna instead of the bottom. The antenna is firstly designed by calculating theoretical values of key parameters, and then optimized by means of 3D full-wave simulation software. Simulation and measurement results show that the optimized antenna offers 6.1% and 3.7% bandwidth at L1 and L2, respectively, with axial ratio bandwidth of more than 1%. The size of the antenna is $73mm{\times}73mm{\times}6.4mm$, which is small and low-profile.

• Journal of Ocean Engineering and Technology
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• v.32 no.5
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• pp.402-409
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• 2018

This paper describes the plan and procedure of a development test and evaluation that will be performed to verify the performance and technology of multi-mission unmanned surface vehicles (MMUSVs). In order to verify the design requirement of MMUSVs, we designed and manufactured the common platform of MMUSVs, which have an overall length of8.4 m, a displacement of 3,100 kg, and a speed of more than35 kts. The platform is equipped with several sub-systems, including radar and an EOTS/IRS. The EOTS/IRS, along with the search radar, is used for effective detection, identification, and targeting. The core technologies of MMUSV for DT&E will be investigated. The common platform design technologies, remote operating and control system technologies, autonomous navigation technologies, and unmanned operational technology of sensors and equipment will be studied for the development of the MMUSV's core technologies. The system will be able to make precise observations and track targets both manually and automatically during day and night conditions. Currently, the verification tests for each of the technologies and for the integrated system are in the pipeline for DT&E, which will be performed next year. Also, software reliability and life tests will be performed.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3710-3717
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• 1999

For the development of unmanned autonomous vehicle, it is essential to detect obstacles, especially vehicles, in the forward direction of navigation. In order to reliably exclude regions that do not contain obstacles and save a considerable amount of computational effort, it is often necessary to confine computation only to ROI(region of interest)s. A ROI is usually chosen as the interior region of the lane. We propose a computationally simple and efficient method for the detection of lanes based on Hough transform and quadratic curve fitting. The proposed method first employs Hough transform to get approximate locations of lanes, and then applies quadratic curve fitting to the locations computed by Hough transform. We have experimented the proposed method on real outdoor road scene. Experimental results show that our method gives accurate detection of straight and curve lanes, and is computationally very efficient.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.400-403
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• 2021

Algorithms for predicting the optimal route of vehicles are being actively sudied with the recent development of autonomous driving technology. Companies such as SK, Kakao, and Naver provide services that navigate the optimal route. They predicts the optimal path with information from the users in real time. However, they can predict the optimal route, but not optimal lane route. We proposes a system that navigates the optimal lane path with coordinates data from vehicles using Lidar sensor. The proposed method is a system that guides smooth lanes by acquiring time series coordinate data of a vehicle after performing the Lidar-based object detection method. we demonstrates the performance using actual acquired data from the experimental results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.821-828
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• 2011

This paper developed the algorithm for improving the performance the auto pilot in the autonomous vehicle system consisting of the Track keeping control, the Automatic steering, and the Automatic mooring control. The automatic steering is the control device that could save the voyage distance and cost of fuel by reducing the unnecessary burden of driving due to the continuous artificial navigation, and avoiding the route deviation. During the step of the ship autonomic navigation control, since the wind power or the tidal force could make the ship deviate from the fixed course, the automatic steering calculates the difference between actual sailing line and the set course to keep the ship sailing in the vicinity of intended course. first, we could get the transfer function for the modeling of ship according to the Nomoto model. Considering the maneuverability, we propose it as linear model with only 4 degree of freedoms to present the heading angle response to the input of rudder angle. In this paper, the model of ship is derived from the simplified Nomoto model. Since the proposed model considers the maximum angle and rudder rate of the ship auto pilot and also designs the Fuzzy controller based on existing PID controller, the performance of the steering machine is well improved.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.