• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.487-495
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• 2023

This paper presents a method for autonomous exploration of indoor environments using a 2-dimensional Light Detection And Ranging (LiDAR) scanner. The proposed frontier-based exploration method considers navigability from the current robot position to extracted frontier targets. An approach to constructing the point cloud grid map that accurately reflects the occupancy probability of glass obstacles is proposed, enabling identification of safe frontier grids on the safety grid map calculated from the point cloud grid map. Navigability, indicating whether the robot can successfully navigate to each frontier target, is calculated by applying the skeletonization-informed rapidly exploring random tree algorithm to the safety grid map. While conventional exploration approaches have focused on frontier detection and target position/direction decision, the proposed method discusses a safe navigation approach for the overall exploration process until the completion of mapping. Real-world experiments have been conducted to verify that the proposed method leads the robot to avoid glass obstacles and safely navigate the entire environment, constructing the point cloud map and calculating the navigability with low computing time deviation.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.36-41
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• 2011

Configuration space(C-space) including configuration obstacle(C-obstacle) is one of the most important concepts in mobile robot path planning. Using C-space and C-obstacles, the robot with different shapes and moving mechanisms can be considered as a point in the C-space. And, as a result, the collision-free path for the robot can be easily achieved. To make C-space including C-obstacle, many researchers used circular approximation method for the efficient caluculation time. This method can help us to save our time by approximating the shape of a robot as the minimum sized circle which can cover all the area of robot. But, by using the circle larger than the robot, more space are considered as the part of robot and, as a result, some obstacles which are very near each other may be considered as a combined one obstacle. To solve this problem, multi-level configuration space is proposed by this paper. This multi-level method also use the circular approximation method as the initial step. But, after finding the initial path, it will check how many obstacles are combined. And then, for each combined obstacle, more accurate C-space generation will be continued. To check the efficiency of the proposed algorithm, time for c-space generation are compared with the well-known accurate C-space generation method using various types of robot shape.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.174-179
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• 2003

Through the simultaneous localization and map building (SLAM) technique, a robot can create maps about its unknown environment while it continuously localizes its position. Grid maps and feature maps have been widely used for SLAM together with application of probability methods and POMDP (partially observed Markov decision process). But this approach based on grid maps suffers from enormous computational burden. Topological maps, however, have drawn more attention these days because they are compact, provide natural interfaces, and are easily applicable to path planning in comparison with grid maps. Some topological SLAM techniques like GVG (generalized Voronoi diagram) were introduced, but it enables the robot to decide only whether the current position is part of GVG branch or not in the GVG algorithm. In this paper, therefore, to overcome these problems, we present a method for updating a global topological map from the local topological maps. These local topological maps are created through a labeled Voronoi diagram algorithm from the local grid map built based on the sensor information at the current robot position. And the nodes of a local topological map can be utilized as the features of the environment because it is robust in light of visibility problem. The geometric information of the feature is applied to the extended Kalman filter and the SLAM in the indoor environment is accomplished. A series of simulations have been conducted using a two-wheeled mobile robot equipped with a laser scanner. It is shown that the proposed scheme can be applied relatively well.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.158-164
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• 2015

Lane detection is one of the key parts among autonomous vehicle technologies because lane keeping and path planning are based on lane detection. Camera is used for lane detection but there are severe limitations such as narrow field of view and effect of illumination. On the other hands, Lidar sensor has the merits of having large field of view and being little influenced by illumination because it uses intensity information. Existing researches that use methods such as Hough transform, histogram hardly handle multiple lanes in the co-occuring situation of lanes and road marking. In this paper, we propose a method based on RANSAC and regularization which provides a stable and precise detection result in the co-occuring situation of lanes and road marking in highway scenarios. This is performed by precise lane point extraction using circular model RANSAC and regularization aided least square fitting. Through quantitative evaluation, we verify that the proposed algorithm is capable of multi lane detection with high accuracy in real-time on our own acquired road data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.9-21
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• 2018

In South Korea, Jeju Island has a role as a test bed for electric vehicles (EVs). All conventional cars on the island are supposed to be replaced with EVs by 2030. Accordingly, how to effectively set up EV charging stations (EVCSs) that can charge EVs is an urgent research issue. In this paper, we present a case study on planning the locations of EVCS for Jeju Island, South Korea. The objective is to determine where EVCSs to be installed so as to balance the load of EVCSs while satisfying demands. For a public service with EVCSs by some government or non-profit organization, load balancing between EVCS locations may be one of major measures to evaluate or publicize the associated service network. Nevertheless, this measure has not been receiving much attention in the related literature. Thus, we consider the measure as a constraint and an objective in a mixed integer programming model. The model also considers the maximum allowed distance that drivers would detour to recharge their EV instead of using the shortest path to their destination. To solve the problem effectively, we develop a heuristic algorithm. With the proposed heuristic algorithm, a variety of numerical analysis is conducted to identify effects of the maximum allowed detour distance and the tightness of budget for installing EVCSs. From the analysis, we discuss the effects and draw practical implications.

• Journal of Astronomy and Space Sciences
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• v.22 no.3
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• pp.263-272
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• 2005

For the Communication, Ocean and Meteorological Satellite (COMS) which will be launched in 2008, an algorithm for finding the precise location of the sun-glint point on the ocean surface is studied. The precise locations of the sun-glint are estimated by considering azimuth and elevation angles of Sun-satellite-Earth geometric position and the law of reflection. The obtained nonlinear equations are solved by using the Newton-Raphson method. As a result, when COMS is located at $116.2^{\circ}E$ or $128.2^{\circ}E$ longitude, the sun-glint covers region of ${\pm}10^{\circ}(N-S)$ latitude and $80-150^{\circ}(E-W)$ longitude. The diurnal path of the sun-glint in the southern hemisphere is curved towards the North Pole, and the path in the northern hemisphere is forwards the south pole. The algorithm presented in this paper can be applied to predict the precise location of sun-glint region in any other geostationary satellites.

• Journal of Korean Society of Disaster and Security
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• v.13 no.2
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• pp.53-63
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• 2020

In this study, the two-dimensional flow analysis model Hydro_AS-2D model was used to simulate the situation of flooding in Seongsangu and Uichang-gu in Changwon in the event of rising sea levels and extreme flooding, and the results were expressed on three-dimensional topography and the optimal evacuation path was derived using BIM technology. Climate change significantly affects two factors in terms of flood damage: rising sea levels and increasing extreme rainfall ideas. The rise in sea level itself can not only have the effect of flooding coastal areas and causing flooding, but it also raises the base flood level of the stream, causing the rise of the flood level throughout the stream. In this study, the rise of sea level by climate change, the rise of sea level by storm tidal wave by typhoon, and the extreme rainfall by typhoon were set as simulated conditions. The three-dimensional spatial information of the entire basin was constructed using the information of topographical space in Changwon and the information of the river crossing in the basic plan for river refurbishment. Using BIM technology, the target area was constructed as a three-dimensional urban information model that had information such as the building's height and location of the shelter on top of the three-dimensional topographical information, and the results of the numerical model were expressed on this model and used for analysis for evacuation planning. In the event of flooding, the escape route is determined by an algorithm that sets the path to the shelter according to changes in the inundation range over time, and the set path is expressed on intuitive three-dimensional spatial information and provided to the user.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.10-21
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• 2008

User travel behavior is based on the existence of complete traffic information in deterministic user optimal principle by Wardrop(1952). According to deterministic user optimal principle, users choose the optimal route from origin to destination and they change their routes arbitrarily in order to minimize travel cost. In this principle, users only consider travel time as a factor to take their routes. However, user behavior is not determined by only travel time in actuality. Namely, the models that reflect only travel time as a route choice factor could give irrational travel behavior results. Therefore, the model is necessary that considers various factors including travel time, transportation networks structure and traffic information. In this research, more realistic deterministic optimal traffic assignment model is proposed in the way of route recognizance behavior. This model assumes that when users decide their routes, they consider many factors such as travel time, road condition and traffic information. In addition, route recognizance attributes is reflected in this suggested model by forward searching method and backward searching method with numerical formulas and algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.1063-1076
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• 2017

To improve the productivity of the earthwork, a fleet management system for construction equipment was suggested in previous studies. But there were some gaps between theory and practice. To overcome this problem, some opinions are gathered form experts and field engineers and four improvements have been proposed and reflected in the system. First, the previous system consists of one hardware module, so it is hard to install it at a control office and construction equipment at the same time. The server module for the office and the mobile module for construction equipment are separately developed. Second, the transportation algorithm that is used in the previous system can generate shortest paths for the earthwork distribution, but embankment areas are not gathered. This situation leads to a decrease in compaction productivity. A modified algorithm for earthwork distribution is suggested. Third, the automated coordinate transformation is performed to show the position of construction equipment on the 3D terrain in real-time. Fourth, construction equipment groups should be formed in the initial stage of earthwork and the number of equipment of each groups should be changed by operation status and site environment. But this functions did not work properly in the previous system. This problem is corrected in the proposed system. The improvements can make the proposed system much more realistic one and can leads to an increase in the productivity of earthwork operations.