• Journal of Navigation and Port Research
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• v.37 no.4
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• pp.375-381
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• 2013

In order to establish eLoran system it needs the betterment of a receiver and a transmitter, the add of data channel to loran pulse for loran system information and the differential Loran for compensating Loran-c signal. Precise ASF database map is essential if the Loran delivers the high absolute accuracy of navigation demanded at maritime harbor entrance. In this study we developed the ASF mapping method using predicted ASFs compensated by the measured ASFs for maritime in the harbor. Actual ASF is measured by the legacy Loran signal transmitted from Pohang station in the GRI 9930 chain. We measured absolute propagation delay between the Pohang transmitting station and the measurement points by comparing with the cesium clock for the calculation of the ASFs. Monteath model was used for the irregular terrain along the propagation path in the Yeongil Bay. We measured the actual ASFs at the 12 measurement points over the Yeongil Bay. In our ASF-mapping method we estimated that the each offsets between the predicted and the measured ASFs at the 12 spaced points in the Yeongil. We obtained the ASF map by adjusting the predicted ASF results to fit the measured ASFs over Yeungil bay.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.2
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• pp.53-65
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• 2008

This paper proposes the qualitative method for planning the operation of multi-AUVs with environmental disturbances, which is considered to be a very difficult task. In this paper we use an extension collision map as a collision free motion planner. The tool was originally developed for the multiple ground vehicles with no internal/external disturbance. In order to apply the method to a water environment where there are tides and waves, and currents, we analyze the path deviation error of AUVs caused by external disturbances. And we calculate safety margin for the collision avoidance on the extension collision map. Finally, the simulation result proves that the suggested method in this paper make multi-AUVs navigate to the goal point effectively with no collision among them.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.291-301
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• 2000

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.442-449
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• 2013

In this paper, a simulation system based on X-Plane and MATLAB/Simulink for multiple UAVs is presented. For the conceptual design of this proposed system, a hierarchical system architecture for multiple UAVs is presented. This architecture has object-oriented data structure which consists of three objects (UAV status, mission and task, and environment) and a hierarchy consisting of four layers (decision making layer, task assignment layer, path and motion planning layer, and collision avoidance layer) is also proposed. In addition, this paper shows a implementation of simulation system based on the proposed system architecture using X-Plane and MATLAB/Simulink. The result of simulation from the developed system in this paper validate capability of application for multiple UAVs in real environment.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.1-8
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• 2019

Autonomous vehicles operated in the rough terrain environment must satisfy various technical requirements in order to improve the speed. Therefore, in order to design and implement a technical architecture that satisfies the requirements for speed improvement of autonomous vehicles, it is necessary to consider the overall technology of hardware and software to be mounted. In this study, the technical architecture of the autonomous vehicle operating in the rough terrain environment is presented. In order to realize high speed driving in pavement driving environment and other environment, it should be designed to improve the fast and accurate recognition performance and collect high quality database. and it should be determined the correct running speed from the running ability analysis and the frictional force estimation on the running road. We also improved synchronization performance by providing precise navigation information(time) to each hardware and software.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.210-216
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• 2017

In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.43-50
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• 2014

This paper introduces a robot platform which can do weeding while traveling between rice seedlings stably against irregular land surface of a paddy field. Also, an autonomous navigation technique that can track on stable state without any damage of the seedlings in the working area is proposed. Detection of the rice seedlings and avoidance knocking down by the robot platform is achieved by the sensor fusion of a laser range finder (LRF) and an inertial measurement unit (IMU). These sensors are also used to control navigating direction of the robot to keep going along the column of rice seedling consistently. Deviation of the robot direction from the rice column that is sensed by the LRF is fed back to a proportional and derivative controller to obtain stable adjustment of navigating direction and get proper returning speed of the robot to the rice column.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.252-258
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• 2012

This paper describes hierarchical semantic map building using the classified area information in home environments. The hierarchical semantic map consists of a grid, CAIG (Classified Area Information in Grid), and topological map. The grid and CAIG maps are used for navigation and motion selection, respectively. The topological map provides the intuitive information on the environment, which can be used for the communication between robots and users. The proposed semantic map building algorithm can greatly improve the capabilities of a mobile robot in various domains, including localization, path-planning and HRI (Human-Robot Interaction). In the home environment, a door can be used to divide an area into various sections, such as a room, a kitchen, and so on. Therefore, we used not only the grid map of the home environment, but also the door information as a main clue to classify the area and to build the hierarchical semantic map. The proposed method was verified through various experiments and it was found that the algorithm guarantees autonomous map building in the home environment.

• Knowledge Management Research
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• v.11 no.2
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• pp.75-93
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• 2010

Even though there have been many efforts on driver's route recommendation, driver still should get involved to choose the driving path in a manual manner. Uncertain traffic information provided to the driver delays his arrival time and hence may cause diminished economic values. One of the solutions of reducing the uncertainty is to provide various kinds of traffic information, rather than send real-time information. Therefore, as the wireless communication technology improves and at the same time volume of utilizable traffic contents increases in geometrical progression, selecting traffic information based on driver's context in a timely and individual manner will be needed. Hence, the purpose of this paper is to propose a methodology that efficiently sends the rich traffic contents to the personal in-vehicle navigation. To do so, driver preference is modeled and then the recommendation algorithm of traffic information contents was developed using the preference model. Secondly, ontology based traffic situation analyzation method is suggested to automatically inference the noticeable information from the traffic context on driver's route. To show the feasibility of the idea proposed in this paper, an open API service is implemented in consideration of ease of use.