• Proceedings of the Korea Society for Simulation Conference
• /
• 1999.10a
• /
• pp.100-107
• /
• 1999

무인 운반차량 시스템 (AGV System) 의 이용도가 날로 증가함에 따라 시스템의 최적화 및 운영 방법에 관한 많은 연구가 진행되고 있다. 이에 본 연구에서는 AGV System에서 사용하는 Routing 및 Scheduling 정책들을 연구하고 이를 개선할 수 있는 새로운 방안을 모색한 후, 컴퓨터 모델링 기법을 이용한 보다 객관적인 시뮬레이션을 수행하여 최적의 AGV System과 그에 적합한 운영 정책을 제시하는데 그 목적이 있다. 따라서 본 논문은 크게 AGV Routing 과 Scheduling에 관한 연구로 나누어진다. AGV Routing은 AGV의 이동경로를 설정하는 것으로서 충돌 방지 (Collision Avoidance)와 최단경로 탐색 (Minimal Cost Path Find) 이라는 두 개의 주요 알고리즘으로 이루어진다. AGV Scheduling 은 장비의 공정시간과 AGV의 Loading/Unloading, Charging 시간으로 인해 불규칙한 Event 가 일어났을 경우 AGV 각각의 Jop을 알맞게 선정해주는 정책을 말하며 일반적으로 AGV Selection Rule, Charging Rule이 여기에 속한다. 본 연구에서는 이러한 알고리즘들이 반영된 AGV System을 컴퓨터 모델로 구축하여, 기존 시스템에서 사용되고 있는 여러 운영 정책들의 문제점들을 분석하였으며, Multiple AGV System을 최적화 시키는 운영 정책이 보다 객관적으로 제시되었다.

• IE interfaces
• /
• v.15 no.1
• /
• pp.1-9
• /
• 2002

Tandem AGV system is obtained by partitioning all workstations into multiple zones assigning a single vehicle to each zone. In this paper, we propose an analytical model to design a tandem AGV system with multi-load AGVs. Using simulation, the performance of the proposed model is shown by comparing a conventional multi-load AGV system.

• Journal of the Korea Society for Simulation
• /
• v.3 no.1
• /
• pp.1-16
• /
• 1994

In this paper, the modeling capabilities of an object-oriented simulator, AgvTalk is demonstrated by designing and simulating a conceptually configuration of AGV systems, known as the tandem configuration. The characteristics and design methodology in AgvTalk are described between the tandem configuration for AGV systems and conventional AGV systems. Also, simulation between the conventional AGV system and its corresponding tandem AGV system are compared with AgvTalk in the job shop environment. From the simulation results, the characteristics of each system observed are discussed.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.4
• /
• pp.145-153
• /
• 2021

Automated Guided Vehicle (AGV) is commonly used in manufacturing plant, warehouse, distribution center, and terminal. AGV is self-driven vehicle used to transport material between workstations in the shop floor without the help of an operator, and AGV includes a material transfer system located on the top and driving system at the bottom to move the vehicle as desired. For navigation, AGV mostly uses lane paths, signal paths or signal beacons. Various predominant sensors are also used in the AGV. However, in the conventional AGV, there is a problem of not turning or damaging nearby objects or AGV in a narrow space. In this paper, a new driving system is proposed to move the vehicle in a narrow space. In the proposed driving system, two sets of the combined steering-drive unit are adopted to solve the above problem. A prototype of AGV with the new driving system is developed for the comparative analysis with the conventional AGV. In addition, the experimental result shows the improved performance of the new driving system in the maximum speed, braking distance and positioning precision tests.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.4
• /
• pp.115-121
• /
• 2017

In this paper, the intelligent vision system for an effective and intelligent path-planning of an industrial AGV system based on stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the industrial AGV system and the obstacle detected and the 2D path coordinates obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The industrial AGV system move automatically by effective and intelligent path-planning using the obtained 2D path coordinates. From some experiments on AGV system driving with the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 2% on average, respectably.

• 연구논문집
• /
• s.22
• /
• pp.27-38
• /
• 1992

We deals with stationary layout control system of AGV. It is a intelligent control system to he wholly charged control PC a layout information and guided command and to be controlled a vehicle driving, steering, safety of natural functions of AGV. Fieldbus concentrator of stationary layout control system serves control command from control PC and status information of AGV. Telegram software monitors transmitted command and status information through IR(JnfraRed) modem. Especially it is possible to easily network to use not an exclusive controller of AGV but personal computer(PC) when communicate and interface a different kind of controller.

• Journal of Korea Society of Industrial Information Systems
• /
• v.19 no.2
• /
• pp.59-66
• /
• 2014

AGV is most often used for the automation of freight transportation in the manufacturing industry or the distribution warehouses. AGV is fairly costly and used in goods transport between the determined location. The main control device dedicated to AGV is often autonomously developed for simplification using PLC in industry field. However, AGV developed for simplification makes many errors in traffic because it is developed for the limited simple function. Control device dedicated to AGV has been developed to solve the problem but it is almost impossible to revise the device according to the character and structure of every manufacturing industry. The purpose of this study is to propose the design method of the control system interlocked with PLC and dedicated to AGV. The control system should be to improve the problem of traffic rolling and possible to be revised according to the character of factory. It is apparent the proposed AGV system is efficient in operation in the result of several traffic performance analysis through the tests.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2017.07a
• /
• pp.17-18
• /
• 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 the Korea Society for Simulation
• /
• v.8 no.3
• /
• pp.67-76
• /
• 1999

The study of the optimization of operating policy of AGV system, which is used in many factory automation environments has been proceeded by many researchers. The major operating policy of AGV system consists of routing and scheduling policy. AGV routing is composed with collision avoidance and minimal cost path find algorithm. To allocate jobs to the AGV system, AGV scheduling has to include AGV selection rules, parking rules, and recharging rules. Also in these rules, the key time parameters such as processing time of the device, loading/unloading time and charging time should be considered. In this research, we compare and analyze several operating policies of multiple loop-multiple AGV system by making a computer model and simulating it to present an appropriate operating policy.

• 전자공학회논문지 IE
• /
• v.46 no.1
• /
• pp.23-30
• /
• 2009

In this paper, the intelligent vision system for an effective and intelligent path-planning of an industrial AGV system based on stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the industrial AGV system and the obstacle detected and the 2D Path coordinates obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The industrial AGV system move automatically by effective and intelligent path-planning using the obtained 2D path coordinates. From some experiments on AGV system driving with the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 2.5% on average, respectably.