• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.293-294
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• 2013

다양한 생물체의 행동 원리를 이용하여 모델링한 알고리즘을 생체모방 알고리즘(Biologically Inspired Algorithm)이라고 한다. 본 논문에서는 생체모방 알고리즘 중 동물 집단의 행동을 모델링한 플로킹 알고리즘(Flocking Algorithm)을 이용한 집단 게임 캐릭터의 길찾기 방법을 제안한다. 플로킹 알고리즘의 조타행동은 크게 분리(Separation), 정렬(Alignment), 응집(Cohesion), 회피(Avoidance)로 구성되어 있다. 게임에서의 기존 플로킹 알고리즘은 주로 여러 개의 몬스터나 NPC 들로 구성된 몇 개의 그룹 단위로 독자적인 집단 행동을 하는 경우에 적합하다. 그러나, 게임플레이어가 제어하는 캐릭터가 많은 경우, 기존 알고리즘은 플레이어가 선택한 캐릭터 그룹을 목표지점으로 이동하는 방법으로 적합하지 않다. 따라서 본 논문에서는 게임 플레이어가 제어하는 집단 게임캐릭터의 목표 지점까지의 길찾기를 위한 수정된 정렬 조타행동 알고리즘을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.190-192
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• 2006

게임의 장르가 다양해지고 대규모의 온라인 게임이 가능해 징에 따라 게임 환경과 더불어 게임 안에 등장하는 캐릭터의 수도 많아지고 있다. 게이머에 의해 움직이는 캐릭터 외에도 여러 종류의 다양한 NPC(Non-Player Character)들이 각각 맡은 임무를 띠고 각기 움직이게 된다. 본 논문에서는 NPC들의 자연스러운 이동을 위해 제안된 일반화 가시성그래프를 이용하여 계획된 경로의 효과적인 구현을 위한 조타행동(steering behaviors)과 경로 이동 중에 만나는 다른 캐릭터에 대한 NPC들의 조타행동을 정의하고 구현하여 이동에 따른 효율을 실험해 본다.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.105-114
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• 2011

The roadmap-based planning is a path planning method which is used widely for a goal-directed movement in Robotics and has been applied to the world of computer animation such as computer games. However it is unnatural for computer characters to follow the path planned by the roadmap method as it is performed in Robotics. Flocking which is used for realistic and natural movements in computer animation enables character's movement by using a few simple rules without planning unlike the roadmap method. However it is impossible to achieve a goal-directed movement with flocking only because it does not keep states. In this paper we propose a simulation method which combines planning based on the road map with reactive actions for natural movements along the path planned. We define and implement steering behaviors for a leader which are needed to follow the trajectory naturally by analysing characteristics of roadmap-based paths and for the rest of members which follow the leader in various manners by detecting obstacles. The simulations are performed and demonstrated by using the implemented steering behaviors on every possible combination of roadmap-based path planning methods and models of configuration spaces. We also show that the detection of obstacle-collisions can be done effectively because paths are planned in the configuration space in which a moving object is reduced to a point.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.6
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• pp.701-708
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• 2018

Human error is an important cause of maritime accidents and the identification of human error is fundamental to maritime-accident preventions. In particular, the pattern of technical behavior taken in the circumstance of bridge teams(navigator & helmsman) provides important information to identify human error. The purpose of this study is to identify and analyze technical behavior pattern of bridge teams using Williamson's turn for rescue of persons overboard. The focus of this study is to build and analyze a cognitive model of the human behavior factors of the bridge teams in the process of implementing the experiments. The experimental environment was constructed using a ship-handling simulator and conducted an experiment on participants from 24 bridge teams. As a result of the experiment, it was able to identify the behavior pattern of the ship's maneuvering and maintain trajectory using the rudder and engine. This study is expected to correct human error in the bridge teams application to the certification and training of seafarers.