• Journal of Advanced Navigation Technology
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• v.19 no.2
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• pp.116-122
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• 2015

Motivated by continuous increase in flight demand, awareness of the importance in developing ways to increase aircraft operational efficiency on the airport movement area has been raised. This paper proposes a new routing algorithm for providing the shortest path in a right time, enhancing the aircraft movement efficiency. Many researches on developing algorithms have been performed, for example, Dijkstra algorithm and $A^*$ algorithm. The Dijkstra algorithm provide optimal solution but could possibly provide it with a cost of relatively longer computation time. On the other hand, $A^*$ algorithm does not guarantee the optimality of a solution. In this paper, we suggest a Hybrid $A^*$ algorithm, incorporating both algorithms to eliminate the weaknesses. Rigorous test shows the proposed Hybrid $A^*$ algorithm may achieve shorter computing time and optimality in searching the shortest path.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.24-34
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• 2011

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for human. UA V s are currently employed in many military missions such as reconnaissance, surveillance, enemy radar jamming, decoying, suppression of enemy air defense (SEAD), fixed and moving target attack, and air-to-air combat. UAVs also are employed in a number of civilian applications such as monitoring ozone depletion, inclement weather, traffic congestion, and taking images of dangerous territory. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$-PGA (A-star with Post Smoothing-Parallel Genetic Algorithm) for an UAV's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and TSP (Traveling Salesman Problem). A path planning algorithm for UAV is applied by transforming MRPP into SPP (Shortest Path Problem).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.301-305
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• 2001

Conventionally, robot control algorithms are divided into two stages, namely, path or trajectory planning and path tracking(or path control). This division has been adopted mainly as a means of alleviating difficulties in dealing with complex, complex, coupled manipulator dynamics. The minimum-time manipulator control problem is solved for the case when the path is specified and the actuator torque limitations are known. In path planning, DP is applied to applied to find the shortest path form initial position to final position with the assumptions that there is no obstacle and that each path is straight line. In path control, the phase plane technique is applied to the minimum-time control with the assumptions that the bound on each actuator torque is a function of joint position and velocity or constant. This algorithm can be used for any manipulator that has rigid link, known dynamics equations of motion, and joint angles that can be determined at a given position on the path.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.3
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• pp.281-287
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• 2023

Establishing a ship's passage plan is an essential step before it starts to sail. The research related to the automatic generation of ship passage plans is attracting attention because of the development of maritime autonomous surface ships. In coastal water navigation, the land, islands, and navigation rules need to be considered. From the path planning algorithm's perspective, a ship's passage planning is a global path-planning problem. Because conventional global path-planning methods such as Dijkstra and A^* are time-consuming owing to the processes such as environmental modeling, it is difficult to modify a ship's passage plan during a voyage. Therefore, the D^* algorithm was used to address these problems. The starting point was near Busan New Port, and the destination was Ulsan Port. The navigable area was designated based on a combination of the ship trajectory data and grid in the target area. The initial path plan generated using the D^* algorithm was analyzed with 33 waypoints and a total distance of 113.946 km. The final path plan was simplified using the Douglas-Peucker algorithm. It was analyzed with a total distance of 110.156 km and 10 waypoints. This is approximately 3.05% less than the total distance of the initial passage plan of the ship. This study demonstrated the feasibility of automatically generating a path plan in coastal navigation for maritime autonomous surface ships using the D^* algorithm. Using the shortest distance-based path planning algorithm, the ship's fuel consumption and sailing time can be minimized.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.140-148
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• 2012

For autonomous navigation, map, pose tracking, and finding the shortest path are required. Because there is no GPS signal in indoor environment, the current position should be recognized in the 3D map by using image processing or something. In this paper, we explain 3D map creation technology by using depth camera like Kinect and pose tracking in 3D map by using 2D image taking from camera. In addition, the mechanism of avoiding obstacles is discussed.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.257-260
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• 2001

Routing region modeling methods for PCB auto-routing system in Shape based type(non-grid method) used region process type and the shape located in memory as a individual element, and this element consumed small memory due to unique data size. In this paper we design PCB(Printed Circuit Board) auto-routing system using the auction algorithm method that 1) Could be reached by solving the shortest path from single original point to various destination, and 2) Shaped based type without any memory dissipation with the best speed. Also, the auto-routing system developed by Visual C++ in Window environment, and can be used in IBM Pentium computer or in various individual PC system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.399-405
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• 2002

Now days, it is based on GIS and GPS, it can search for the shortest path and estimation of arrival time by using the internet and cell phone to driver. But, even though good car navigation system does not create which is the shortest path when there average vehicle speed is 10 -20 Km. Therefore In order to reduce vehicle waiting time and average vehicle speed, we suggest optimal green time algorithm using fuzzy adaptive control , where there are different traffic intersection length and lane. In this paper, it will be able to forecast the optimal traffic Information, estimation of destination arrival time, under construction road, and dangerous road using internet.

• Annual Conference of KIPS
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• 2013.05a
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• pp.403-406
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• 2013

오버레이 멀티캐스트는 IP멀티캐스트에 비해 지연시간이나 대역폭 사용의 측면에 있어서 비효율적이다. 실시간 방송 서비스에서 사용자들에게 QoS를 보장하기 위해 오버레이 멀티캐스트의 이런 비효율성을 줄여야할 필요가 있다. 본 연구에서는 각 호스트들의 제한된 자원과 네트워크 환경을 고려하여 실시간 방송 서비스에 적합한 오버레이 멀티캐스트 트리를 구성하는 알고리즘을 제안하고 적용하여 시뮬레이션한다.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.133-142
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• 2011

Overhead facility design problem(OFDP) is one of the shortest rectilinear flow network problem(SRFNP)[4]. Genetic algorithm(GA), artificial immune system(AIS), population management genetic algorithm (PM) and greedy randomized adaptive search procedures (GRASP) were introduced to solve OFDP. A path matrix formed individual was designed to represent rectilinear path between each facility. An exchange crossover operator and an exchange mutation operator were introduced for OFDP. Computer programs for each algorithm were constructed to evaluate the performance of algorithms. Computation experiments were performed on the quality of solution and calculations time by using randomly generated test problems. The average object value of PM was the best of among four algorithms. The quality of solutions of AIS for the big sized problem were better than those of GA and GRASP. The solution quality of GRASP was the worst among four algorithms. Experimental results showed that the calculations time of GRASP was faster than any other algorithm. GA and PM had shown similar performance on calculation time and the calculation time of AIS was the worst.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.89-96
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• 2007

The amount of home deliveries are increasing day by day owing to the increment of the on-line market. This environment brings along generating many delivery companies and keen competition with each other in its customer hold Therefore, this study aims at the development of a shortest delivery route search demonstration system using Ant Algorithm. The developed system reduces the time consumption significantly in search of delivery path and time of the products for the novice delivery driver as well as experienced driver. Ultimately, the developed system will give the customer reliability and satisfaction, knowing a delivery route in advance.