• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.87-99
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• 2015

In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs) and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle $A^*$ algorithm ($FAA^*$), an advanced $A^*$ algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.514-521
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• 2004

A routing is the path that an actual train set follows as it moves from one train to another train in a timetable. The number of routings is equivalent to the number of trainsets required to cover the timetable. The primary factors of rolling stock requirement plan include evaluating the minimum number of routings. This can be formulated as a set partitioning problem and solved using enumeration method or column generation method. In this paper we presents an enumeration algorithm which is useful to implement the enumeration method for the rolling stock requirement plan.

• 한국노년학
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• v.31 no.4
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• pp.871-884
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• 2011

Standard Long-term care(LTC) Utilization Plan is a kind of care plan, which aims to help beneficiaries and their family choose services to meet their care needs. The objective of this study is to determine the relationships among family caregivers' perceived quality, overall satisfaction and utilization in Standard LTC Utilization Plan. Data were gathered from family caregivers with beneficiaries who have used community service in long-term care insurance system. A national cross-sectional descriptive survey was conducted in December 2008, using proportionate quota sampling. Finally, 351 family caregivers completed questionnaires which included demographic characteristics, perceived quality(9 items), overall satisfaction(1 item) and utilization(2 items). Path analysis was conducted to find a causal relationship. This study shows firstly, the quality of Standard LTC Utilization Plan was categorized into three dimensions, that is, assessment of care needs, recommended care plan, and management of monthly benefits. Secondly, reliability and validity of quality items were satisfied. Finally, in the effect of perceived quality and satisfaction for utilization, assessment of care needs(indirect effect, path coefficients=0.077) and overall satisfaction(total effect, path coefficients=0.324) were statistically significant. The findings of this study would be helpful in developing the strategies, which is needed to improve the role of Standard LTC Utilization Plan.

• Journal of Biosystems Engineering
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• v.24 no.4
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• pp.301-308
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• 1999

Path planning for field operation of agricultural machinery is an indispensible part for precision farming or autonomous field operation. In this study, two algorithms (I, II) of generating a time-based shortest operation path were suggested to plan an optimal operation of an agricultural tractor-implement in a rectangular shaped field. The algorithms were based on modification of a minimum spanning tree algorithm, and applied for tractor-implement operations. the generated path was consisted of round operation and returning operation sections. The number of round operation was determined from the condition that a tractor can turn smoothly at headlands. The performance of the algorithms was evaluated by the calculation number for path generation and the total path length generated. Their stability was affected by the number of returning operation, but the algorithm II was considered to be more stable. In addition, the performances of the developed algorithms were compared with those of the conventional field operations at selected field sizes and shapes. The results showed that the algorithms could reduce field operation time greatly. For a 100m$\times$40m field, the reduced path length was 78m. The study also included an user interface program for implementing the algorithms and generating GPS coordinates that could be used in GIS softwares for precision farming.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.327-334
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• 2011

It is necessary that UGV(Unmanned Ground Vehicle) should generate a real-time travesability index map by analyzing raw terrain information to travel autonomously tough terrain which has various slope and roughness values. In this paper, we propose a local path planning method, $MA^*$(Modified $A^*$) algorithm, using DVGM (Directional Velocity Grid Map) for unmanned ground vehicle. We also present a path optimization algorithm and a path smoothing algorithm which regenerate a pre-planned local path by $MA^*$ algorithm into the reasonable local path considering the mobility of UGV. Field test is conducted with UGV in order to verify the performance of local path planning method using DVGM. The local path planned by $MA^*$ is compared with the result of $A^*$ to verify the safety and optimality of proposed algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1479-1485
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• 2015

Robot's technology was very simple and repetitive in the past. Nowadays, robots are required to perform intelligent operation. So, path planning has been studied extensively to create a path from start position to the goal position. In this paper, potential field algorithm was used for path planning in dynamic environments. It is used for a path plan of mobile robot because it is elegant mathematical analysis and simplicity. However, there are some problems. The problems are collision risk, avoidance path, time attrition. In order to resolve path problems, we amalgamated potential field algorithm with the artificial neural network system. The input of the neural network system is set using relative velocity and location between the robot and the obstacle. The output of the neural network system is used for the weighting factor of the repulsive potential function. The potential field algorithm problem of mobile robot's path planning can be improved by using artificial neural network system. The suggested algorithm was verified by simulations in various dynamic environments.

• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.201-213
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• 2022

Creation and administration of green space are emphasized to solve the environmental problem and the management of green space in urban area. Urban area with high development pressure faces green space fragmentation, so the planned approach is needed to improve the continuity of green space. However, the current institutional green axis, used to enhance continuity of urban space is merely an abstract concept under the master plan so that is not a consistent framework for urban green continuity providing no detailed information such as position and path. Therefore, in order to consistently manage green space in continuous point of view, it is insufficient not being connected to each individual green space development projects. This study proposes a method for finding the connection path to enhance urban green space continuity. This proposed method consists of two phases. First phase is finding nodes to connect current green space and second is to calculate the least cost path. We calculate connection cost using NDMI (Normalized Difference Moisture Index), impervious ratio and official land cost, applying to Suwon city and potential greening site that was planned in official master plan. According to the results, we confirm a possibility of finding a cost-effective connection path with detailed spatial information instead of unrealistic abstract concepts and discuss worth applying to a legally plan and policy.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.651-658
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• 2011

An efficient modified $D^*$ lite algorithm is suggested, which can perform online path planning for mobile robots in dynamic indoor environment. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on $D^*$ Lite algorithm, we improved representation of edge cost, heuristic function, and priority queue management, to build a modified $D^*$ Lite algorithm. Performance of the proposed algorithm is revealed via extensive simulation study.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.7
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• pp.73-80
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• 2009

This paper describes a path planning algorithm, which is the minimal turning path based on the shape and size of the cell to clean up the whole area with two cleaning robots. Our method divides the whole cleaning area with each cell by cellular decomposition, and then provides some path plans among of the robots to reduce the rate of energy consumption and cleaning time of it. In addition we suggest how to plan between the robots especially when they are cleaning in the same cell. Finally simulation results demonstrate the effectiveness of the algorithm in an unknown area with multiple robots. And then we compare the performance index of two algorithms such as total of turn, total of time.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.252-254
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• 2005

Completer coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots and painter robots. In this paper, a novel Water Flowing Algorithm (WFA) is proposed for cleaning robots to complete coverage path planning in unknown environment without obstacles. The robot covers the whole workspace just like that water fills up a container. First the robot goes to the lowest point in the workspace just like water flows to the bottom of the container. At last the robot will come to highest point in the workspace just like water overflows from the container and simultaneously the robot has covered the whole workspace. The computer simulation results show that the proposed algorithm enable the robot to plan complete coverage paths.