• IE interfaces
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• v.2 no.1
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• pp.37-45
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• 1989

Guide path design is the most important factor in planning automated guided vehicle systems(AGVS) in manufacturing shop environments. This paper studies a heuristic procedure to design an optimal bi-directional guide path with the objective of the minimum total travel time of the vehicles. An example is solved to validate the procedure developed.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1996.10a
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• pp.199-204
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• 1996

It is discssed how to detrmine the home location of vhicles in an AGVS with a loop guidepath in a way of maximizing the request-call response probabilities for all demand. Optimal home position is selected by solving the simultaneous equations easily . Statuc positioning strategy is analyzed in which a single home position is allocated to which every vehicle is outed whenever it becomes idle. The cases of unidirectional guidepath is considered only. We provide a numerical example to illustrate the search algorithm developed for the case and compare the searched optimal solutions with the others.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.421-436
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• 1999

It is discussed how to locate idle vehicles of AGVS considering dynamically changing situation. Several positioning methods are suggested including static positioning, dynamic positioning with time-independent pickup probabilities, dynamic positioning with time-dependent pickup probabilities, and dynamic positioning with a look-ahead capability. These positioning strategies are compared with each other by a simulation experiment.

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.723-733
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• 2005

This paper presents a deadlock avoidance method for AGVs in automated container terminals. For a more efficient use of AGV traveling area, we divided the area into small-sized grids not enough to cover a whole AGV. Our deadlock avoidance method controls AGVs by identifying strongly connected components(SCCs) in a graph derived from the paths of AGVs on the grids. Also in this paper we suggest a route selection scheme which selects a route by predicting and comparing travel times of candidate routes by using a regression formula. Simulation experiments have shown that the proposed method can control AGVs for 48 hours without deadlocks and the count of AGV visits per QC is increased by $2\~10$ an hour.

• Journal of Navigation and Port Research
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• v.35 no.6
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• pp.501-507
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• 2011

This paper focuses on dispatching strategy for AGVs(Automated Guided Vehicle). The goal of AGV dispatching is assigning AGVs to requested job to minimizing the delay of QCs and the travel distance of AGVs. Due to the high dynamic nature of container terminal environment, the effect of dispatching is hard to predict thus it leads to frequent modification of dispatching decisions. In this situation, approaches based on a single rule are widely used due to its simplicity and small computational cost. However, these approaches have a limitation that cannot guarantee a satisfactory performance for the various performance measures. In this paper, dispatching strategy based on multicriteria heuristics is proposed. The Proposed strategy consists of multiple decision criteria. A multi-objective evolutionary algorithm is applied to optimize weights of those criteria. The result of simulation experiment shows that the proposed approach outperforms single rule-based dispatching approaches.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.281-288
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• 2022

AGVs are often used in industrial applications to transport heavy materials around a large industrial building, such as factories or warehouses. In particular, in fulfillment centers their usefulness is maximized for automation. To increase productivity in warehouses such as fulfillment centers, sophisticated path planning of AGVs is required. We propose a scheme that can be applied to QMIX, a popular cooperative MARL algorithm. The performance was measured with three metrics in several fulfillment center layouts, and the results are presented through comparison with the performance of the existing QMIX. Additionally, we visualize the transport paths of trained AGVs for a visible analysis of the behavior patterns of the AGVs as heat maps.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.85-101
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• 1995

Automated Guided Vehicles(AGVs) are widely used in computer integrated manufacturing(CIM) systems for material handling purposes. Although automated guided vehicles provide higher levels of flexibility and computer integrability, the installations are limited in number and one of the critical reasons lies in the complexity involved in the operation. The main objective of this research is to alleviate this problem by proposing efficient integrated operational control methods for AGV-based CIM systems. Particularly, this research is concerned with the mixed problem of dispatching automated guided vehicles and scheduling machines operation. The proposed dynamic heuristic algorithm uses various priority schemes and relevant information concerning the load of the system, the status of queues, and the position of AGVs in the scheduling process. The scheduling decision process is hierarchical in the sense that different decision criteria are applied sequentially to identify the most appropriate part to be served. This algorithm consists of two sections, the section of part selection by AGVs for the next service whenever an AGV completes the current assignment, and the section of part selection by machines for next service whenever a machine completes the current operation. The proposed algorithm has been compared with other scheduling schemes using the performance measure of mean flow-time and mean tardiness. Simulation results indicate that the proposed algorithm can reduce the mean flow-time and mean tardiness significantly.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.140-146
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• 2013

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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• pp.307-314
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• 2013

We designed and implemented a fork-type automatic guided vehicle (AGV) with a laser guidance system. Most previous AGVs have used two types of guidance systems: magnetgyro and wire guidance. However, these guidance systems have high costs, are difficult to maintain with changes in the operating environment, and can drive only a pre-determined path with installed sensors. A laser guidance system was developed for addressing these issues, but limitations including slow response time and low accuracy remain. We present a laser guidance system and control system for AGVs with laser navigation. For analyzing the performance of the proposed system, we designed and built a fork-type AGV, and performed repetitions of our experiments under the same working conditions. The results show an average positioning error of 51.76 mm between the simulated driving path and the driving path of the actual fork-type AGV. Consequently, we verified that the proposed method is effective and suitable for use in actual AGVs.

• Proceedings of the Korea Association of Information Systems Conference
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• 1996.11a
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• pp.199-204
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• 1996

It is discussed how to determine the home location of idle vehicles in an AGVS with a loop guide path in a way of maximizing the request-call response probabilities for all demand. Optimal home position is selected by solving the simultaneous equations easily. Static positioning strategy is analyzed in which a single home position is allocated to which every vehicle is routed whenever it becomes idle. The cases of unidirectional guidepath is considered only. We provide a numerical example to illustrate the search algorithm developed for the case and compare the searched optimal solutions with the others.