• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.55-61
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• 2020

In this paper, we present a novel approach to efficiently control the location of NPC(Non-playable characters) in the interactive virtual world such as game, virtual reality. To control the NPC's movement path, we first calculate the main trajectory based on the user's path, and then move the NPC based on the weight map. Our method constructs automatically a navigation mesh that provides new paths for NPC by referencing the user trajectories. Our method enables adaptive changes to the virtual world over time and provides user-preferred path weights for smartagent path planning. We have tested the usefulness of our algorithm with several example scenarios from interactive worlds such as video games, virtual reality. In practice, our framework can be applied easily to any type of navigation in an interactive world.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.1
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• pp.23-30
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• 2012

Purpose: There was a problem with using MU verification programs for the reasons that there were errors of MU when using MU verification programs based on Pencil Beam Convolution (PBC) Algorithm with radiation treatment plans around lung using Analytical Anisotropic Algorithm (AAA). On this study, we studied the methods that can verify the calculated treatment plans using AAA. Materials and Methods: Using Eclipse treatment planning system (Version 8.9, Varian, USA), for each 57 fields of 7 cases of Lung Stereotactic Body Radiation Therapy (SBRT), we have calculated using PBC and AAA with dose calculation algorithm. By developing MU of established plans, we compared and analyzed with MU of manual calculation programs. We have analyzed relationship between errors and 4 variables such as field size, lung path distance of radiation, Tumor path distance of radiation, effective depth that can affect on errors created from PBC algorithm and AAA using commonly used programs. Results: Errors of PBC algorithm have showned $0.2{\pm}1.0%$ and errors of AAA have showned $3.5{\pm}2.8%$. Moreover, as a result of analyzing 4 variables that can affect on errors, relationship in errors between lung path distance and MU, connection coefficient 0.648 (P=0.000) has been increased and we could calculate MU correction factor that is A.E=L.P 0.00903+0.02048 and as a result of replying for manual calculation program, errors of $3.5{\pm}2.8%$ before the application has been decreased within $0.4{\pm}2.0%$. Conclusion: On this study, we have learned that errors from manual calculation program have been increased as lung path distance of radiation increases and we could verified MU of AAA with a simple method that is called MU correction factor.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.141-147
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• 2015

In this study, a position control algorithm for an omni-directional mobile robot based on Mecanum wheels was introduced and experimentally evaluated. Multiple ultrasonic sensors were installed around the mobile robot to obtain position feedback. Using the distance of the robot from the wall, the position and orientation of the mobile robot were calculated. In accordance with the omni-directional velocity generation mechanism, the velocity kinematics between the Mecanum wheel and the mobile platform were determined. Based on this formulation, a simple and intuitive position control algorithm was suggested. To evaluate the control algorithm, a test bed composed of artificial walls was designed and implemented. While conventional control algorithms based on normal wheels require additional path planning for two-dimensional planar motion, the omni-directional mobile robot using distance sensors was able to directly follow target positions with the simple proposed position feedback algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2225-2239
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• 2021

To assist in data collection, the use of a mobile sink has been widely suggested in the literature. Due to the limited sensor node's storage capacity, this manner to collect data induces huge latencies and drop packets. Their buffers will be overloaded and lead to network congestion. Recently, a new bio-inspired optimization algorithm appeared. Researchers were inspired by the swarming mechanism of salps and thus creating what is called the Salp Swarm Algorithm (SSA). This paper improves the sink mobility to enhance energy dissipation, throughput, and convergence speed by imitating the salp's movement. The new approach, named the Mobile Sink based on Modified Salp Swarm Algorithm (MSSA), is approved in a heterogeneous Wireless Sensor Network (WSN) data collection. The performance of the MSSA protocol is assessed using several iterations. Results demonstrate that our proposal surpass other literature algorithms in terms of lifespan and throughput.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.869-872
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• 2003

This paper presents a geometric machining simulation algorithm to enhance the reliability and user-friendliness of a comprehensive computer aided process planning (CAPP) system by verifying generated NC data. In order to represent the complex machining geometry with high accuracy, the proposed algorithm is developed based on a boundary representative (B-rep) solid modelling kernel. Solid models are used to represent the part geometry. tool swept volume and material removal volume by Boolean unite and subtract operations. By integrating a machining simulation procedure into the CAPP system, the systematic analysis of the tool path can be implemented synthetically. To demonstrate and check the validity of suggested system, a simple example of simulation is represented and the result is discussed.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.486-488
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• 2012

본 논문에서는 로보틱스나 컴퓨터 게임 등의 다양한 분야에서 일반적으로 존재하는 동적인 환경에서 장애물 회피를 위한 경로 계획 알고리즘을 연구하였다. 제안하는 알고리즘은 전역 경로계획과 지역 경로계획의 두 단계로 이루어져 있고, A*와 가시성 그래프에 의해 구해진 전역 경로를 이동할 때에 동적 장애물을 감지하게 되면 이를 회피하기 위해 포텐샬장으로 지역 경로를 구성한다. 이 알고리즘은 포텐샬장을 A*와 결합함으로써 지역 최적화 문제를 해결하고 포텐샬장만으로 이동하는 경우에 비해 시간적인 측면에서도 더욱 효율적이다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.132-133
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• 2015

Efficient scheduling and resource management are the key factor to reduce construction project budget (e.g., labor cost, equipment cost, material cost, etc.). Resource-based line of balance (LOB) technique has been used to complement the limitations of time-driven scheduling techniques (e.g., critical-path method). Optimizing construction alternatives contributes cost savings while honoring the project deadline. However, existing LOB scheduling is lack of identifying optimal resource combination. This study presents a method which identifies the optimal construction alternatives, hence achieving resource minimization in a repetitive construction by using genetic algorithm (GA). The method provides efficient planning tool that enhances the usability of the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.354-360
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• 1998

In general, it is very difficult to find optimal fuzzy rules by experience when a system is dynamical and/or complex. Futhermore proper fuzzy partitioning is not deterministic and there is no unique solution. Therefore we propose a new design method of an optimal fuzzy logic controller, that is a co-evolutionary genetic algorithm finding optimal fuzzy rule and proper membership functions at the same time. We formalize the relation between fuzzy rules and membership functions in terms of fitness. We review the typical approaching methods to co-evolutionary genetic algorithms , and then classify them by fitness relation matrix. Applications of the proposed method to a path planning problem of autonomous mobile robots when moving objects exist are presented to demonstrate the performance and effectiveness of the method.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2453-2455
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• 2003

We propose a path planning method to reduce the inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.412-414
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• 2019

경로 계획은 에이전트가 로봇이 특정 목적지에 도착할 수 있도록 에이전트가 수집한 정보를 바탕으로 경로를 설정하는 작업을 뜻한다. 부분 관측만 가능한 맵인 경우 에이전트 이동마다 새로 수집되는 정보들을 바탕으로 마르코프 의사결정 과정을 사용한 가치 반복 알고리즘이 널리 사용되지만, 제안된 가치 반복 알고리즘 사용 시 매 행동마다 모든 공간의 최적 경로를 계산하기 때문에 시간이 오래 걸리는 문제점이 있다. 이에 본 논문에서는 에이전트가 한 번에 탐색하는 범위가 제한되어 있다는 점에 착안하여 탐색 반경 내에 속하는 공간의 가치 함수 값을 미리 추정하여 효율적으로 최적의 경로를 추정하는 가치 반복 알고리즘을 제안한다.