• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.23-36
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• 1990

A unit-load automated guided vehicle system is considered in which a single vehicle is operated on a unidirectional path in a closed loop. The vehicle serves a manufacturing cell moving pallets from one station to another based on the "First-Encountered-First-Serve" dispatching rule. An approximation method is developed to compute the mean waiting time of an arbitrary pallet at each station. Extensive numerical experiments, performed for various problems, yield fairly good results in most of the cases compared with those obtained by simulation method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.287-297
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• 1997

This research is concerned with operation control problem for an automated manufacturing system which consists of two machine centers and a single automatic guided vehicle. The objective is to develop and evaluate heuristic scheduling procedures that minimize maximum completion time to be included travel time of AGV. A new heuristic algorithm is proposed and a numerical example illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions than the previous algorithms.

• Journal of the KSME
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• v.34 no.2
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• pp.101-111
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• 1994

이 글에서는 무인운반차(AGV: Automated Guided Vehicle), 자동창고 (AS/RS: Automated Storage/Retrieval System), 콘베이어시스템, 바코드시스템 등의 자동물류취급시스템을 응용하여 극단적인 다품종 소량생산체제의 납기단축효과와 가동효율을 어떻게 향상시킬 수 있는지를 저 자들이 직접주도하여 설계 . 설치 . 가동중인 사례를 통하여 실증적으로 밝혀보고자 한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.151-151
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• 2000

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.88.1-88
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• 2002

$\textbullet$ Introduce $\textbullet$ Basic principle and kinematics model of the AGV $\textbullet$ Design of the guidance system $\textbullet$ Simulation and experimentation $\textbullet$ Conclusion

• Korean Management Science Review
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• v.11 no.1
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• pp.1-21
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• 1994

We usually use the simulation technique in the evaluation and the test of a design alternative of Automated Guided Vehicle System. In this paper, we introduce a simulation code generator which can assist simulation programmer in model development and programming. It consists of user interface, program editor, and program sorter. SIMAN is used as the target language.

• Journal of Navigation and Port Research
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• v.28 no.7
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• pp.635-640
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• 2004

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.539-547
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• 2016

Automated guided vehicles (AGVs) are widely used in industry. Several types of vision-based AGVs have been studied in order to reduce cost of infrastructure building at floor of workspace and to increase flexibility of changing the navigation path layout. A practical vision-based guideline tracing method is proposed in this paper. A virtual tracing wheel is introduced and adopted in this method, which enables a vision-based AGV to trace a guideline in diverse ways. This method is also useful for preventing damage of the guideline by enforcing the real steering wheel of the AGV not to move on the guideline. Usefulness of the virtual tracing wheel is analyzed through computer simulations. Several navigation tests with a commercial AGV were also performed on a usual guideline layout and we confirmed that the virtual tracing wheel based tracing method could work practically well.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.121-139
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• 1992

AGVS(Automated Guided Vehicle Systems) in material handling have been used widely since late 1970s. Implementation of an AGVS generally requires substantial study to optimize the design and performance of guide-paths. Traditional mathematical approaches have been used with limited success to analyze AGVS. These approaches, however, do not provide a practical tool for guide-path designers. This paper presents a new approach based on rules in designing and assessing AGV guide-paths to improve the design of a closed-loop layout. A framework for the integrated approach is proposed, problem solving procedures are explained, and a case study is reported to demonstrate the framework. Deletion of seldom used guide-paths, and addition of bypasses to solve the congestion problem, are conducted interactively and iteratively through simulation experiments. To visualize the results, a graphic control program is developed and integrated with the AutoMod/AutoGram simulation package.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.291-301
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• 2000

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.