• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.646-655
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• 2009

This paper presents a new search strategy based on models of evolution in order to solve the problem of collision-free robotic path planning. We designed the robot path planning method with genetic algorithm which has become a well-known technique for optimization, intelligent search. Considering the path points as genes in a chromosome will provide a number of possible solutions on a given map. In this case, path distances that each chromosome creates can be regarded as a fitness measure for the corresponding chromosome. The effectiveness of the proposed genetic algorithm in the path planning was demonstrated by simulation. The proposed search strategy is able to use multiple and static obstacles.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.1-8
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• 2020

In this paper, we propose an optimal path search algorithm between each node and midpoint that applies the time weighting. Services for using a location of mid point usually provide a mid point location-based on the location of users. There is a problem that is not efficient in terms of time because a location-based search method is only considered for location. To solve the problem of the existing location-based search method, the proposed algorithm sets the weights between each node and midpoint by reflecting user's location information and required time. Then, by utilizing that, it is possible to search for an optimum path. In addition, to increase the efficiency of the search, it ensures high accuracy by setting weights adaptively to the information given. Experimental results show that the proposed algorithm is able to find the optimal path to the midpoint compared with the existing method.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.21-31
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• 2005

In state-of-the-art games, characters can move in a goal-directed manner so that they can move to the goal position without colliding obstacles. Many path-finding methods have been proposed and implemented for these characters and most of them use the A* search algorithm. When .the map is represented with a regular grid of squares or a navigation mesh, it often takes a long time for the A* to search the state space because the number of cells used In the grid or the mesh increases for higher resolution. Moreover the A* search on the grid often causes a zigzag effect, which is not optimal and realistic. In this paper we propose to use visibility graphs to improve the search time by reducing the search space and to find the optimal path. We also propose a method of taking into account the size of moving characters in the phase of planning to prevent them from colliding with obstacles as they move. Simulation results show that the proposed method performs better than the grid-based A* algorithm in terms of the search time and space and that the resulting paths are more realistic.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.8
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• pp.74-84
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• 2010

In this paper, we propose a preference-based shortest path algorithm which is combined with Ant Colony Optimization (ACO) and A* heuristic algorithm. In recent years, with the development of ITS (Intelligent Transportation Systems), there has been a resurgence of interest in a shortest path search algorithm for use in car navigation systems. Most of the shortest path search algorithms such as Dijkstra and A* aim at finding the distance or time shortest paths. However, the shortest path is not always an optimum path for the drivers who prefer choosing a less short, but more reliable or flexible path. For this reason, we propose a preference-based shortest path search algorithm which uses the properties of the links of the map. The preferences of the links are specified by the user of the car navigation system. The proposed algorithm was implemented in C and experiments were performed upon the map that includes 64 nodes with 118 links. The experimental results show that the proposed algorithm is suitable to find preference-based shortest paths as well as distance shortest paths.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.160-163
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• 2021

In this paper, we present a path search scheme for the safe movement of the swarm of unmanned systems in unknown dangerous areas. Some of the swarm searches for the primary and secondary paths before the majority of swarm move through dangerous areas. In terms of rapid movement from the dangerous area and preparation for an accident, the primary path is searched first in the destination's direction. The secondary path is searched by considering the distance between the paths to guarantee a safe distance. The computer simulations show that the proposed scheme is suitable for the swarm of unmanned systems.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2606-2615
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• 1994

Sorting time is one of the most important issues for auto IC test handling systems. In actual system, because of too much path, reducing the computing time for finding a sorting path is the key way to enhancing the system performance. The exhaustive path search technique can not be used for real systems. This paper proposes heuristic sorting algorithm to find the minimal sorting time. The suggested algorithm is basically based on the best-first search technique and multi-level search technique. The results are close to the optimal solutions and computing time is greately reduced also. Therefore the proposed algorthm can be effectively used for real-time sorting process in auto IC test handling systems.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.79-86
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• 2012

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the $A^*$ algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.7
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• pp.889-897
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• 1999

In this paper, we propose a new method of path planning for autonomous mobile robot in mapped circumstance. To search the optimal path, we adopt the genetic algorithm which is based on the natural mechanics of selection, crossover and mutation. We propose a method for generating the path population, selection and evaluation in genetic algorithm. Simulations show the efficiency for the global path planning, if we adopt the proposed GA method

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1444-1451
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• 2016

This paper proposes a Tabu search algorithm to minimize the required energy to send data between a source and a destination using the cooperative communication in wireless ad hoc networks. As the number of nodes in wireless ad hoc networks increases, the amount of calculation for establishing the path between nodes would be too much increased. To obtain the optimal cooperative path within a reasonable computation time, we propose a new Tabu search algorithm for a high-density wireless network. In order to make a search more efficient, we propose some efficient neighborhoods generating operations of the Tabu search algorithm. We evaluate those performances through some experiments in terms of the minimum energy required to send data between a source and a destination as well as the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.351-356
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• 2022

Among the path planning methods used to generate the ship's path, the graph search-based method is widely used because it has the advantage of its completeness, optimality. In order to apply the graph-based search method to the berthing path plan, the deviation from the path must be minimized. Path following suitability should be considered essential, since path deviation during berthing can lead to collisions with berthing facilities. However, existing studies of graph search-based berthing path planning are dangerous for application to real-world navigation environments because they produce results with a course change just before berthing. Therefore, in this paper, we develop a cost function suitable for path following, and propose a 3D A* algorithm that applies it. In addition, in order to evaluate the suitability for the actual operating environment, the results of the path generation of the algorithm are compared with the trajectory of the data collected by manned operations.