• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1374-1381
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• 2022

Under the influence of nuclear radiation, the reliability of steam generators (SGs) is an important factor in the efficiency and safety of nuclear power plant (NPP) reactors. Motion planning that remotely manipulates an SG mobile tube-inspection robot to inspect SG heat transfer tubes is the mainstream trend of NPP robot development. To achieve motion planning, conditional traversal is usually used for base position optimization, and then the A^* algorithm is used for path planning. However, the proposed approach requires considerable processing time and has a single expansion during path planning and plan paths with many turns, which decreases the working speed of the robot. Therefore, to reduce the calculation time and improve the efficiency of motion planning, modifications such as the matrix method, improved parent node, turning cost, and improved expanded node were proposed in this study. We also present a comprehensive evaluation index to evaluate the performance of the improved algorithm. We validated the efficiency of the proposed method by planning on a tube sheet with square-type tube arrays and experimenting with Model SG.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.425-433
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• 2012

Dijkstra's algorithm is one of well-known methods to find shortest paths over a network. However, more research on $A^*$ algorithm is necessary to discover the shortest route to a goal point with the heuristic information rather than Dijkstra's algorithm which aims to find a path considering only the shortest distance to any point for an optimal path search. Therefore, in this paper, we compared Dijkstra's algorithm and $A^*$ algorithm for bicycle route selection. For this purpose, the horizontal distance according to slope angle and average speed were calculated based on factors which influence bicycle route selection. And bicycle routes were selected considering the shortest distance or time-dependent shortest path using Dijkstra's or $A^*$ algorithm. The result indicated that the $A^*$ algorithm performs faster than Dijkstra's algorithm on processing time in large study areas. For the future, optimal path selection algorithm can be used for bicycle route plan or a real-time mobile services.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1911-1919
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• 2012

In this paper, we focus on a robotic sealing process in which three robots are used. Each robot can be considered as a 7 axis redundant robot of which the first joint is prismatic and the last 6 joints are revolute. In the factory floor, robot path planning is not a simple problem and is not automated. They need experienced operators who can operate robots by teaching and playing back fashion. However, the robotic sealing process is well organized so the relative positions and orientations of the objects in the floor and robot paths are all pre-determined. Therefore by adopting robotic theory, we can optimally plan robot pathes without using teaching. In this paper, we analyze the sealing robot by using redundant manipulator theory and propose three different methods for path planning. For sealing paths outside of a car body, we propose two methods. The first one is resolving redundancy by using pseudo-inverse of Jacobian and the second one is by using weighted pseudo-inverse of Jacobian. The former is optimal in the sense of energy and the latter is optimal in the sense of manipulability. For sealing paths inside of a car body, we must consider collision avoidance so we propose a performance index for that purpose and a method for optimizing that performance index. We show by simulation that the proposed method can avoid collision with faithfully following the given end effector path.

• Journal of the Korea Society for Simulation
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• v.16 no.1
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• pp.31-37
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• 2007

The importance of NPC's role in computer games is increasing. An NPC must perform its tasks by perceiving obstacles and other characters and by moving through them. It has been proposed to plan a natural-looking path against fixed obstacles by using a generalized visibility graph. In this paper we develop the execution module for an NPC to move efficiently along the path planned on the generalized visibility graph. The planned path consists of line segments and arc segments, so we define steering behaviors such as linear behaviors, circular behaviors, and an arriving behavior for NPC's movements to be realistic and utilize them during execution. The execution module also includes the collision detection capability to be able to detect dynamic obstacles and uses a decision tree to react differently according to the detected obstacles. The execution module is tested through the simulation based on the example scenario in which an NPC interferes the other moving NPC.

• Journal of Surface Science and Engineering
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• v.34 no.5
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• pp.367-377
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• 2001

Plasma is generated by electrical discharge. Most plasma generation has been carried out at low-pressure gas typically less than one millionth of atmospheric pressure. Plasmas are in general generated from impact ionization of neutral gas molecules by accelerated electrons. The energy gain of electrons accelerated in an electrical field is proportional to the mean free path. Electrons gain more energy at low-pressure gas and generate plasma easily by ionization of neutrals, because the mean free path is longer. For this reason conventional plasma generation is carried out at low pressures. However, many practical applications require plasmas at high-pressure. In order to avoid the requirement for vacuum pumps, researchers in Korea start to develop plasmas in high-pressure chambers where the pressure is 1 atmosphere or greater. Material processing, environmental protection/restoration and improved energy production efficiency using plasmas are only possible for inexpensive bulk plasmas. We thus generate plasmas by new methods and plan to set foundations for new plasma technologies for $21^{st}$ / century industries. This technological research will play a central role in material processing, environmental and energy production industries.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1475-1478
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• 2004

This paper describes map building for the path planning to avoid obstacles with vision sensor and ultrasonic sensor. We get the 2 dimensional information from the processed images of CCD sensor and 1 dimensional range information from ultrasonic sensor. I proposed a way to generate the map which contains these two kinds of information in the program. And we made the biped robot which have 20 DOF with these sensors and get good experimental result to prove the validity of the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1795-1798
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• 2003

This paper presents a method for impeller modeling by the reverse engineering and the 5-axis machining. The impeller is composed of pressure surface, suction surface and leading edge, and so on. The impeller is modeled by using the characteristic curves of impeller such as hub curves, shroud curves and leading edge. The characteristic curves are extracted from the scanned data. The hub curves and shroud curves are generated by intersection between blade surface and hub boundary and shroud boundary. respectively. A sample impeller machining is performed by tool path plan and post-processing with inverse kinematic solution.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.871-874
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• 1996

It is practically very important in multi-criteria long-tenn IRP process to develop the set of candidate resource plans that meet following two conditions. First, the number of resource plans should not be too large for computer job. Second, the unknown best plan should exist among the set of candidate plans. In this paper, several novel procedures are developed. The main idea of the procedures is the two-stage approach. The first stage is to find the set of feasible resource capacity mixes in given target year(s). And, the second stage is to find the set of alternative paths of resource options for each resource mix determined in the first stage.

• Journal of Aerospace System Engineering
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• v.14 no.6
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• pp.1-9
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• 2020

Global e-commerce and delivery companies are actively pursuing last-mile delivery service using drones, and various delivery schedule planning studies have been conducted. In this study, separate individual route networks were constructed to reflect drone route constraints such as prohibited airspace and truck route constraints such as rivers, which previous studies did not incorporate. The A* algorithm was used to calculate the shortest path distance matrix between the starting point and destinations. In addition, we proposed an optimal delivery schedule plan using genetic algorithms and applied it to compare the efficiency with that of vehicle-only delivery.