• 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 the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.18-23
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• 2003

This paper presents new algorithms of path planning and obstacle avoidance for an autonomous mobile robot to navigate under unknown environments in the real time. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. It is shown by computer simulation that these algorithms are working well. Furthermore, an autonomous mobile robot was constructed to implement and test these algorithms in the real field. The experimental results are also satisfactory just like those of computer simulation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.32-38
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• 1999

An autonomous mobile vehicle for transport system must plan optimal path in work envimnrent without human supervision and obstacle collision. This is to reach a destination without getting lost. In this paper, a genetic algorithm for globaI and local path planning and collision avoidance is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The sinmulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.rithms.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.89-99
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• 2011

In this paper, we propose an routing algorithm for ultra low power and high reliable transmission in WBAN environment. This algorithm is to minimize energy consumption and to maximize the life and reliability for medical devices. Also, this algorithm is not only medical devices but also non-medical devices is to minimize energy consumption and to maximize the life of device. The combination of the distance from the previous node and residual energy calculates weight. The calculated weight is used to calculate the weight of full path by cumulative weights. The full path to the smallest of the weights are set to the path. Also this algorithm is able to select another path to avoid the error path by determining the link status between nodes, when occurs link error and congestion. In this paper, we show that WSN routing algorithm based on shortest hop count routing algorithm and EAR routing algorithm compared to ensure high reliability and low power characteristic of WBAN to be verified through simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.943-948
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• 2018

In this paper, we propose a hybrid approach of combining $A^*$ and Genetic algorithm in the path search problem. In $A^*$, the cost from a start node to the intermediate node is optimized in principle but the path from that intermediate node to the goal node is generated and tested based on the cumulated cost and the next node in a priority queue is chosen to be tested. In that process, we adopt the genetic algorithm principle in that the group of nodes to generate the next node from an intermediate node is tested by its fitness function. Top two nodes are selected to use crossover or mutation operation to generate the next generation. If generated nodes are qualified, those nodes are inserted to the priority queue. The proposed method is compared with the original sequential selection and the random selection of the next searching path in $A^*$ algorithm and the result verifies the superiority of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06d
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• pp.58-62
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• 2007

기존의 무선 Ad-hoc 네트워크의 연구는 라우팅기법에 중심으로 이뤄지고 있다. 그러나 기존의 연구들은 네트워크를 구성하는 각 요소들이 우호적이며 상호 협력적인 상황을 가정하여 연구가 이루어지고 있다. 그러나 최근 연구에는 안전한 통신을 보장하기 위한 보안 알고리즘의 필요성에 집중되고 있다. 무선 Ad-hoc 네트워크에서의 악의적인 노드를 식별하는 방안들은 정상적인 노드임에도 불구하고 거짓으로 신고했을 때 확인절차 없이 경로를 재탐색하여 최적의 경로를 변경시킴으로서 최적의 전송환경을 활용하지 못하는 문제점이 있다. 본 논문에서는 다중경로 기반의 보안경로 탐색 프로토콜인 MP-SAR 프로토콜을 이용하여 보안경로에서는 악의적인 노드를 검증하고, 유효한 최단경로를 통해 데이터전송을 하는 기법을 제안하고자 한다. 제안한 기법을 적용함으로써 노드에 대한 신고가 있을 때 확인과정을 거쳐 불필요하게 경로를 재탐색하는 과정을 줄일 수 있다.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.91-103
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• 2008

In order to simulate the behavior of automated manufacturing systems, the performance of material handling systems should be measured dynamically. Multi-Agent technology could be well adapted for the development of simulator for distributed and intelligent manufacture systems. A multi-agent system is composed of one coordination agent and multiple application agents. Issues in AGVS simulator can be classified by the set-up and operating problems. Decisions on the number of vehicles, bi- or uni-directional guide-path, etc. are fallen into the set-up problem category, while deadlock tree algorithm and conflict resolution are in operating problem. In this paper, a multi-agent based deadlock-free simulator for automated guided vehicle system(AGVS) are proposed through the use of multi-agent technologies and the development of deadlock-free algorithm. In this AGVS simulator proposed, well-known Floyd algorithm is used to create AGVS Guide path, through which AGVS move. Also, AGVs avoid vehicle conflict and deadlock using check path algorithm. And Moving vehicle agents are operated in real-time control by coordination agent. AGV position is dynamically calculated based on the concept of rolling time horizon. Simulator receives and presents operating information of vehicle in AGVS Gaunt chart. The performance of the proposed algorithm and developed simulator based on multi-agent are validated through set of experiments.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.69-80
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• 2016

Some studies were conducted for the purpose of minimizing total clearance time for rapid evacuation from the indoor spaces when disaster occurs. Most studies took a long time to calculate the optimal evacuation route that derived minimum evacuation time. For this reason, this study proposes an evacuation route assignment algorithm that can shorten the total clearance time in a short operational time. When lots of exits are in the building, this algorithm can shorten the total clearance time by assigning the appropriate pedestrian traffic volume to each exit and balances each exit-load. The graph theory and greedy algorithm were utilized to assign pedestrian traffic volume to each exit in this study. To verify this algorithm, study used a cellular automata-based evacuation simulator and experimented various occupants distribution in a building structure. As a result, the total clearance time is reduced by using this algorithm, compared to the case of evacuating occupants to the exit within shortest distance. And it was confirmed that the operation takes a short time In a large building structure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.658-660
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• 2004

모바일 멀티미디어 서비스에서는 핸드오프의 효율적인 처리를 통한 QoS를 보장하는 것이 중요하다. 본 논문에서는 기존 핸드오프 기법의 경로 최적화, 회선의 재활용률, 핸드오프 수행시간 등의 문제점을 개선을 위해 Crossover Switch(CX)탐색 기법에 적용되는 기존의 Loose select, Prior path knowledge와 제안한 Hybrid CX 탐색 알고리즘의 성능분석을 위해 C#을 사용하여 시뮬레이터를 구현하고 회선 재이용률, 경로 최적화 정도를 비교분석하였다. 실험결과 제안한 Hybrid CX 탐색 알고리즘이 우수하다는 것을 확인하였다.