• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1117-1123
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• 2005

This paper deals with a new automated guided vehicle (AGV) control system for distributed control. Proposed AGV control system adapts the multi-agent technology. The system is composed of two types of controller: routing and order. The order controller is in charge of assignment of orders to AGVs. Through the bidding-based negotiation with routing controllers, the order controller assigns a new order to the proper AGV. The order controller announces order information to the routing controllers. Then the routing controllers generate a routing schedule for the order and make a bid according to the routing schedule. If the routing schedule conflicts with other AGV's one, the routing controller makes an alternative through negotiation with other routing controllers. The order controller finally evaluates bids and selects one. Each controller consists of a set of agents: negotiation agent, decision making agent and communication agent. We focus on the agent architecture and negotiation-based AGV scheduling algorithm. Proposed system is validated through an exemplary scenario.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.17-18
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• 2017

본 논문은 스마트 팩토리의 중요 요소인 무인반송차(AGV)를 자율 주행시키기 위해 오픈 소스 자율 주행차 시뮬레이터인 udacity를 이용해 머신 러닝시키는 시스템을 개발하였다. 공장의 운행 루트를 자율주행 시뮬레이터의 전경으로 가공하고, 3개의 카메라를 부착시킨 AGV를 운행시키면서 머신 러닝시킨다. AGV를 주행하여 얻어진 여러 학습 데이터를 통해 도출된 결과들을 각각 비교하여 우수한 모델을 선정하고 운행시킨 결과 AGV가 정해진 운행 루트를 정확하게 주행하는 것을 확인하였다. 이를 통해, 가상 운행 환경에서 저비용으로 AGV 운행 학습이 가능하다는 것을 보였다.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.473-479
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• 2009

This paper proposes an efficient method to locate the automated guided vehicle (AGV) into a specific parking position using artificial visual landmark and vision-based algorithm. The landmark has comer features and a HSI color arrangement for robustness against illuminant variation. The landmark is attached to left of a parking spot under a crane. For parking, an AGV detects the landmark with CCD camera fixed to the AGV using Harris comer detector and matching descriptors of the comer features. After detecting the landmark, the AGV tracks the landmark using pyramidal Lucas-Kanade feature tracker and a refinement process. Then, the AGV decreases its speed and aligns its longitudinal position with the center of the landmark. The experiments showed the AGV parked accurately at the parking spot with small standard deviation of error under bright illumination and dark illumination.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.564-569
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• 2007

자동화 컨테이너 터미널에서 안벽크레인, AGV(Automated Guided Vehicle)와 같은 하역장비의 작업은 수 많은 요인에 영향을 받으며, 이로 인해 각 장비의 작업시간을 정확하게 추정하는 것은 거의 불가능하다. 작업시간의 불확실성은 AGV 배차를 어렵게 만들고 작업효율을 떨어뜨리는 주요 원인이다. 본 논문에서는 이러한 불확실성에 대처하기 위하여 확률적 시뮬레이션 기반 AGV 배차 알고리즘을 제안한다. 제안 방안은 AGV를 배차할 때, 이후 일정 기간 동안의 AGV작업에 대해 확률적 시뮬레이션을 여러번 반복하여 수행하고 평가 값을 평균함으로써 불확실성의 영향을 줄인다. 확률적 시뮬레이션을 위해 크레인 작업시간의 불확실성을 간단한 확률함수로 모델링하고 그에 따라 크레인 작업시간을 결정한다. 또한 AGV 작업시간을 가감속, 간섭을 고려하여 추정한다. 시뮬레이션 실험을 통해 제안방안을 검증한 결과 안벽크레인의 지연이 감소함을 확인하였다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.40-48
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• 2022

An automated material handling system (AMHS) has been emerging as an important factor in the semiconductor wafer manufacturing industry. In general, an automated guided vehicle (AGV) in the Fab's AMHS travels hundreds of miles on guided paths to transport a lot through hundreds of operations. The AMHS aims to transfer wafers while ensuring a short delivery time and high operational reliability. Many linear and analytic approaches have evaluated and improved the performance of the AMHS under a deterministic environment. However, the analytic approaches cannot consider a non-linear, non-convex, and black-box performance measurement of the AMHS owing to the AMHS's complexity and uncertainty. Unexpected vehicle congestion increases the delivery time and deteriorates the Fab's production efficiency. In this study, we propose a Q-Learning based dynamic routing algorithm considering vehicle congestion to reduce the delivery time. The proposed algorithm captures time-variant vehicle traffic and decreases vehicle congestion. Through simulation experiments, we confirm that the proposed algorithm finds an efficient path for the vehicles compared to benchmark algorithms with a reduced mean and decreased standard deviation of the delivery time in the Fab's AMHS.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.2
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• pp.43-51
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• 1993

This paper describes the flow path design of unidirectional automated guided vehicle systems. The objective is to find the flow path which will minimize total travel time of unloaded as well as loaded vehicles. The allocation of unloaded vehicles is determined by applying the transportation simplex method. The problem is solved using a branch-and-bound technique. A simple illustrative example is discussed to demonstrate the procedure.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.343-357
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• 1997

This paper proposes a new AGV dispatching algorithm which is suitable for heterarchical manufacturing control structure. It is developed on the basis of bidding concept utilizing the information of work-in-process in incoming and outgoing buffers of workstation, and travel time of AGV. Since the bidding functions are functions of two parameters, sensitivity test is performed to find their appropriate values. The performance of the algorithm is compared with those of well-known existing rules in terms of system throughput through simulation on a hypothetical job shop type manufacturing system.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.59-65
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• 1990

In the design of AGVS (Automated Guided Vehicle Systems), one of the important problem is to determine the number of AGVs required to provide a given level of transport service. At present, there are two kind of methods to determine the number of AGVs, the one is to use the mathematical model, the other is to use the simulation technique. Among these, simulation based technique is more reliable than analytical method. In this sense, this paper intend to determine the optimal number of AGVs using personal computer simulation by SIMAN Ver.3.5.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.837-844
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• 2008

In an automated container terminal, various factors affect the operation of container handling equipment such as quay cranes and AGVs, and thus calculating the exact operation time is nearly infeasible. This uncertainty makes it difficult to dispatch AGVs well. In this paper, we propose a simulation-based AGV dispatching algorithm When dispatching an AGV to an operation, the proposed algorithm conducts multiple stochastic simulation for the succeeding AGV operations for the predetermined period to collect stochastic samples of the result of the dispatching. In the stochastic simulation, the uncertainty of crane operations is represented as a simple probability distribution and the operation time of a crane is determined according to this. A dispatching option is evaluated by the total delay time of quay cranes which is estimated by averaging the quay crane delay of each simulation In order to collect a sufficient number of samples that guarantee the credibility of the evaluation, we devised a high-speed simulator that simulates AGV operation The effectiveness of the proposed algorithm is validated by simulation experiments.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2901-2903
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• 2000

This thesis deals with study and implementation of Fuzzy controller with observer which can enhance the path-tracking performance of optically guided AGV(Automated Guided Vehicle). The AGV in this thesis is differential drive type and has front-side and rear-side optical sensors. which can identify the guiding path. This controller has excellent disturbance rejection and therefore is advantageous when it is instructed to follow straight paths. This fuzzy controller with observer enhances transient performance of the controller is demonstrated by simulation and is compared with that of individual loop controller