• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 추계학술대회 논문집
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• pp.140-145
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• 2005

The dynamic performances of railway vehicles, such as ride comfort, stability and safety, have the opposite characteristics of response each other according to design changes of suspensions. For this reasons, it is necessary that multidisciplinary engineers join in design processes of the suspensions so as to satisfy the requirements of dynamic performance with design constraints. Sometimes iterative dynamic analyses are required so many times during the design processes. In this paper, the development of integrated process environments and the dynamic analyses of railway vehicles based on the environments are presented. Using agent and wrapping technologies, process managements about the work process and design parameters were set up under the distributed computing environments. Also, dynamic analyses on the sample railway vehicle were carried out and the efficiency and improvement in future work were discussed as results.

• 전기학회논문지
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• 제66권1호
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• pp.114-120
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• 2017

The work present in this paper deals with a navigation problem for multiple mobile robots in unknown indoor environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. The environments simulated in this work are dynamic ones which contain not only static but also moving obstacles. In order to guide the robot to move along a collision-free path and reach the goal, this paper presented a navigation method based on fuzzy approach. Then genetic algorithms were applied to optimize the membership functions and rules of the fuzzy controller. The simulation results verified that the proposed method effectively addresses the mobile robot navigation problem.

• 한국정밀공학회지
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• 제20권11호
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.825-836
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• 2019

One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

• 한국컴퓨터정보학회논문지
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• 제11권4호
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• pp.119-125
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• 2006

네트워크를 통하여 서로 연결된 컴퓨팅 자원들의 집합을 분산 시스템이라고 정의할 수 있다. 최적화 문제 영역에서 가장 중요한 해결 기법 중에 하나인 병렬 유전자 알고리즘은 분산 시스템을 기반으로 하고 있다. 인터넷과 이동 컴퓨팅과 같은 동적 네트워크 환경 하에서 네트워크의 상태는 가변적으로 변할 수 있어 기존의 병렬 유전자 알고리즘을 분산 시스템에서 최적화 문제를 해결하기 위하여 그대로 사용하기에는 비효율적이다. 본 논문에서는 동적 네트워크 환경 하에서 분산 에이전트를 사용하여 병렬 유전자 알고리즘을 효율적으로 사용할 수 있는 기법을 제시한다.

• Earthquakes and Structures
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• 제11권6호
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• pp.1043-1060
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• 2016

The engineering background of this article is an ancient wooden building with extremely high historic and cultural values in Tibet. A full understanding of the dynamic behaviour of this historic building under in-service environments is the basis to assess the condition of the structure, especially its responses to earthquake, environmental and operational loading. A dynamic monitoring system has been installed in the building for over one year and the large amounts of high quality data have been obtained. The paper aims at studying the dynamic behaviour of the wooden building in seismic and operational conditions using the field monitoring data. Specifically the effects of earthquake and crowd loading on the structure's dynamic response are investigated. The monitoring data are decomposed into principal components using the Singular Spectrum Analysis (SSA) technique. The relationship between the average acceleration amplitude and frequencies of the principle components and operational conditions has been discussed. One main contribution is to understand the health condition of complex ancient building based on large databases collected on the field.

• 대한수학교육학회지:학교수학
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• 제11권2호
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• pp.281-299
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• 2009

본 논문에서는 동적조작 환경 속에서 이루어지는 물리적 실험을 도구로 선택하여 발명되고 있는 과정으로서의 수학을 학생들이 접할 수 있도록 1) 정의 도입 방식을 변화시켜 의미 있는 수학적 정의를 만들어내는 2) 시각화를 통한 연속성 사고 능력을 강화하는 3) 발견과 탐구를 통하여 수학을 만들어내는 4) 문제를 제기하고 일반화하는 능력을 강화하는 사례들을 제시하고 분석함으로써 수학교과과정에 어떻게 동적조작 환경을 융합시킬 수 있는가를 보였다. 이러한 교수-학습 환경 하에서 발생할 수 있는 문제점을 분석하고, 이러한 문제점을 해결하기 위한 교사의 역할에 대해 논하였다.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권10호
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• pp.605-610
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• 2017

분산 환경에서 특정 서버에 발생한 부하 또는 서버 간의 통신으로 발생한 부하를 해결하기 위한 동적 분할이 필요하다. 이종 환경에서 기존 동적 분할 기법은 물리적 성능이 작은 서버에도 동일한 부하를 분배하므로 질의 응답시간이 늦어지는 문제가 발생한다. 본 논문에서는 이종 환경에서 대용량 RDF 데이터를 위한 동적 분할 기법을 제안한다. 제안하는 기법은 부하 분산을 위해 질의 빈도수와 질의에 사용된 정점 수를 가지고 질의 부하를 계산한다. 또한, 이종 환경에서 물리적 성능이 작은 서버에 적은 부하를 할당하기 위하여 서버들의 물리적 성능을 고려한 서버 부하를 계산한다. 부하 분산 시 서버 간의 통신량을 줄이기 위해 간선 절단 수가 최소가 되도록 동적 분할을 수행한다. 성능 평가를 통해 제안하는 동적 분할 기법이 기존 동적 분할 기법에 비해 우수함을 입증한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.181-183
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• 2006

This paper proposes an intelligent decision framework for update of the environment model using GSPN(generalized stochastic petri nets). The GSPN has several advantages over direct use of the Markov Process. The modeling, analysis, and performance evaluation are conducted on the mathematical basis. By adopting the probabilistic approach, our decision framework helps the robot to decide the time to update the map. The robot navigates autonomously for a long time in dynamic environments. Experimental results show that the proposed scheme is useful for service robots which work semi-permanently and improves dependability of navigation in dynamic environments.