Deadlock prevention for automated guided vehicles in automated container terminals

Automated guided vehicles (AGVs) are an important component for automating container terminals. When utilizing AGVs to transport containers from one position to another in a container terminal, deadlocks are a serious problem that must be solved before real operations can take place. This study assumes that the traveling area for AGVs is divided into a large number of grid-blocks, and, as a method of traffic control, grid-blocks are reserved in advance when AGVs are running. The first purpose of the reservation is to make room between AGVs and to prevent deadlocks. The objective of this study is to develop an efficient deadlock prediction and prevention algorithm for AGV systems in automated container terminals. Because the size of an AGV is much larger than the size of a grid-block on a guide path, this study assumes that an AGV may occupy more than one grid-block at a time. This study proposes a method for reserving grid-blocks in advance to prevent deadlocks. A graphical representation method is suggested for a reservation schedule and a priority table is suggested to maintain priority consistency among grid-blocks. It is shown that the priority consistency guarantees deadlock-free reservation schedules for AGVs to cross the same area at the same time. The proposed method was tested in a simulation study.     

Scheduling and routing algorithms for AGVs: A survey

Automated guided vehicles (AGVs) are now becoming popular in automated materials handling systems, flexible manufacturing systems and even container handling applications. In the past few decades, much research has been devoted to the technology of AGV systems and rapid progress has been witnessed. As one of the enabling technologies, scheduling and routing of AGVs have attracted considerable attention. Many algorithms for the scheduling and routing of AGVs have been proposed. However, most of the existing results are applicable to systems with a small number of AGVs, offering a low degree of concurrency. With a drastically increased number of AGVs in recent applications (e.g. in the order of a hundred in a container handling system), efficient algorithms are needed to resolve the increased contention of resources (e.g. path, loading and unloading buffers) among AGVs. This survey paper first gives an account of the emergence of the problem of AGV scheduling and routing. It then differentiates it from several related problems and classifies major existing algorithms for the problem. Finally, the paper points out fertile areas for future study of AGV scheduling and routing.     

基于路段时间窗考虑备选路径的AGV路径规划

针对自动化集装箱码头基于卸箱任务的自动导引车（automated guided vehicle,AGV）路径规划问题,结合最优路径数学模型、路径搜索方法和时间窗,提出了一种基于路段时间窗的AGV路径规划方法。首先,在给AGV下派任务的基础上,用最优路径数学模型为AGV规划出最短路径;其次,用路径搜索方法搜索AGV的备选路径,在路径长度相同的情况下,按照路径中转折次数确定备选路径优先级,转折次数少的备选路径优先级高;最后,在各AGV最短路径下,设置各个路段的时间窗,时间窗无重叠则表明AGV无冲突,对于时间窗重叠的路段,采用在原路径上插入时间窗或者在备选路径上插入时间窗的方法,再进行时间窗重叠测试,若还存在重叠的,则继续调整至最终实现多AGV的无冲突路径规划。为了验证方法的有效性,以8台AGV分区同时工作为例,用实例证明所提出的路径规划方法的避碰效果。结果显示该方法能为多台同时工作的AGV规划出一条无冲突优化路径,并且用时较短;在试验中发现选择在备选路径上插入时间窗的方法效果更好。研究表明所提方法能有效实现AGV的避碰,提高AGV利用率和自动化集装箱码头的运作效率。     

An AGV routing policy reflecting the current and future state of semiconductor and LCD production lines

This paper presents an efficient policy for AGV and part routing in semiconductor and LCD production bays using information on the future state of systems where AGVs play a central role in material handling. These highly informative systems maintain a great deal of information on current and near-future status, such as the arrival and operation completion times of parts, thereby enabling a new approach for production shop control. Efficient control of AGVs is vital in semiconductor and LCD plants because AGV systems often limit the total production capacity of these very expensive plants. With the proposed procedure, the cell controller records the future events chronologically and uses this information to determine the destination and source of parts between the parts' operation machine and temporary storage. It is shown by simulation that the new control policy reduces AGV requirements and flow time of parts.     

A neural algorithm for finding the shortest flow path for an automated guided vehicle system

The automated guided vehicle (AGV)system is emerging as the dominant technology to maximize the flexibility of material handling, while increasing the overall productivity of manufacturing operations. This paper presents a new way of finding the shortest flow path for an AGV system on a specific routing structure. An optimal solution of the system is determined by using an approach based on the Hopfield neural network with the simulated annealing (SA) procedure. In other words, the proposed approach reduces the total cost of an AGV delivery path from one workstation to another on the shop floor. By changing the temperature of the two-stage SA, a solution can be found that avoids potential collisions between AGVs. Both the flow path and the potential collision, which are major problems in AGV systems, may be solved simultaneously by the proposed neural network approach. Other advantages offered by the proposed method are its simplicity compared with operations research (OR)methods and a decreased number of needed AGVs. The performance of the approach is also investigated.     

Navigation method utilizing floor-integrated inductive power supply modules for omnidirectional AGVs

This paper answers the research question: Can the contactless induced energy supply from a novel inductive floor be used to navigate omnidirectional automated guided vehicles (AGVs)?

In contrast to existing systems a novel inductive floor enables AGVs traveling through production without charging breaks. This floor consists of tiles with inductive modules, which supply the AGV with energy. In addition to supplying power to the AGV, the inductive modules are also intended to guide the vehicle through production. To enable such a guidance sensors placed in the AGV measure the induced voltages of the floor. To answer the research question these voltages are calculated with the help of an electromagnetic simulation of the AGV’s travel on the inductive tiles. To estimate the position as well as rotation of the AGV depending on the simulated voltages as inputs a novel algorithm is presented. During the travel the AGV is able to move in arbitrary directions independently of its orientation. To control the omnidrectional AGV consistently without singularities, a transformation in Omni-Curve-Parameters (OCP) is proposed. As simulation case study a four wheeled steering- and velocity controlled AGV is introduced. For the evaluation a novel motion model depending on the input OCP is presented. This model is compared to the estimation of the position to verify the accuracy and the reproducibility of the algorithm.

     

A bi-directional path layout for conflict-free routing of AGVs

Automated Guided Vehicles (or AGVs for short) are now widely used in automated material handling systems. Much research has been done on developing path layout and algorithms for the optimal routing and scheduling of AGVs. However, with the drastically increased number of AGVs in some recent applications (e.g. in the order of a hundred in container terminals), algorithms that can achieve a high degree of concurrency of AGV moves are urgently needed. This paper presents a bi-directional path layout and an algorithm for routing AGVs. To route the vehicles without conflicts and to minimize the space requirement of the layout, critical conditions for certain key parameters of the path and vehicle are derived. We further show theoretically that a high degree of concurrency of AGV moves can be achieved, although the routing decision takes only a constant amount of time for each vehicle. The routing efficiency is analysed in terms of the distance traversed and the time requirement for AGVs to complete all pickup and drop-off (or P/D for short) jobs. Results of this study could form a basis for more complicated path layouts and routing algorithms.     

考虑冲突避免的多AGV路径规划研究

目的 提高物流企业“货到人”拣选系统在实际生产中的工作效率，避免自动导引小车(AGV)间的冲突死锁，研究大规模多AGV的无冲突路径规划和协同避障问题。方法 首先考虑AGV空载、负载情况和路径扩展成本，改进A^*算法，动态调整代价函数，优化路径扩展方式。其次，提出冲突检测及避免算法，对可能产生局部冲突的路径交叉点进行避障调度，通过预约锁格，实现局部冲突的检测，制定优先级避障策略，解决AGV动态行驶路径上产生的局部冲突和死锁，进而实现全局无冲突路径规划。结果 对多组不同任务量和不同AGV规模的场景进行仿真，实验结果表明，考虑冲突避免的改进A^*算法能有效实现100个任务、90个货架单位和7个拣选站场景下的多AGV动态路径规划，相较于传统A^*算法，其平均拣选时长缩短了52.61%。结论 该方法可实现大规模场景下的多AGV动态路径规划，在付出较小转弯代价的同时有效避免局部动态冲突，该方法可为相关企业实现多AGV协同调度提供新的思路和理论依据。     

Guide path design and location of load pick-up/drop-off points for an automated guided vehicle system

The guide path layout for an automated guided vehicle system (AGVS) is a critical component in the overall design of a flexible manufacturing system (FMS) that utilizes AGVs for materials handling. Not only does it affect the total distance travelled by the vehicles but it also affects vehicle requirements and space utilization. In this study, the problem of selecting the guide path as well as the location of pick-up and drop-off points for outward and inward bound parts to departments is addressed. The problem is modelled and solved as a linear integer program with the objective of minimizing the total distance travelled.     

基于动态时间窗的泊车系统路径规划研究

针对智能立体停车库中自动导引运输车(automated guided vehicle,AGV)存取车路径规划问题,采用分时利用策略,将Dijkstra算法和时间窗法有效结合,提出了一种基于动态时间窗的泊车系统路径规划方法。首先,通过引入优先级策略为接收任务的AGV设定优先级;其次,采用Dijkstra算法,按照任务优先级高低次序,依次为接受任务的AGV规划出最短可行路径;最后,在已知AGV可行路径基础上,通过对可行路径各路段的时间窗进行初始化、实时更新以及实时排布处理,实现多AGV的无冲突路径规划。为验证所提方法的可行性和有效性,以4台AGV同时工作的智能立体停车库为实例进行仿真测试。结果显示:所提出的路径规划方法不仅有效解决了目前多AGV路径规划柔性差、易出现死锁、碰撞冲突等问题,而且可在有效解决路径冲突的前提下,为接受任务的AGV规划出一条时间最短的优化路径。所提方法具有较好的鲁棒性和柔性,有效提高了智能立体停车系统整体运行效率,降低了存取车等待时间。     

A simulation study on the performance of task-determination rules and delivery-dispatching rules for multiple-load AGVs

In this paper, the control problem of multiple-load automated guided vehicles (AGVs) is studied. A control process that identifies four problems faced by multiple-load AGVs is proposed. The first problem is the task-determination problem, in which a multiple-load AGV determines whether its next task is a pickup task or a delivery task. The second problem is the delivery-dispatching problem, in which a multiple-load AGV determines which delivery point it should visit next if its next task is a delivery task. The third problem is the pickup-dispatching problem, in which a multiple-load AGV determines which pickup point it should visit next if its next task is a pickup task. Finally, the fourth problem is the load-selection problem, which requires a multiple-load AGV to determine which load it should pick up from the output queue of a pickup point. This paper focuses on the first and second problems. Different task-determination rules and delivery-dispatching rules are proposed for these two problems. For the problems that are not the main focus of this study, rules found in the literature or real systems are adopted in this study. The objective of this study is twofold. First, we need to understand how well the proposed rules will perform in different performance measures, e.g. the system's throughput and the mean lateness of parts. Second, we need to understand the mutual effects that different types of rules have on each other, so that the best combination of rules can be identified. Computer simulations were conducted to test the performance of the proposed rules. It is hoped the knowledge learned from this study can be beneficial to real multiple-load AGV systems similar to the one studied here.     

Strategies for dispatching AGVs at automated seaport container terminals

Control of logistics operations at container terminals is an extremely complex task, especially if automated guided vehicles (AGVs) are employed. In AGV dispatching, the stochastic nature of the handling systems must be taken into account. For instance, handling times of quay and stacking cranes as well as release times of transportation orders are not exactly known in advance. We present a simulation study of AGV dispatching strategies in a seaport container terminal, where AGVs can be used in single or dual-carrier mode. The latter allows transporting two small-sized (20 ft) or one large-sized (40 ft) container at a time, while in single-mode only one container is loaded onto the AGV irrespective of the size of the container. In our investigation, a typical on-line dispatching strategy adopted from flexible manufacturing systems is compared with a more sophisticated, pattern-based off-line heuristic. The performance of the dispatching strategies is evaluated using a scalable simulation model. The design of the experimental study reflects conditions which are typical of a real automated terminal environment. Major experimental factors are the size of the terminal and the degree of stochastic variations. Results of the simulation study reveal that the pattern-based off-line heuristic proposed by the authors clearly outperforms its on-line counterpart. For the most realistic scenario investigated, a deviation from a lower bound of less than 5% is achieved when the dual-load capability of the AGVs is utilized.     

Dispatching multi-load AGVs in highly automated seaport container terminals

This paper is concerned with AGV dispatching in seaport container terminals. Special attention is given to multi-load vehicles which can carry more than one container at a time. The characteristics of this complex application environment and the impact on the AGV dispatching problem are analyzed and various solution techniques considered. For practical application within an online logistics control system, a flexible priority rule based approach is developed, making use of an extended concept of the availability of vehicles. For evaluation reasons, this approach is complemented by an alternative MILP formulation. Finally, the performance of the priority rule based approach and the MILP model are analysed for different scenarios with respect to total lateness of the AGVs. The main focus of the numerical investigation is on evaluating the priority rule based approach for single and dual-load vehicles as well as comparing its performance against the MILP modelling approach.     

Load selection of automated guided vehicles in flexible manufacturing systems

This paper examines the operation of multiple-load AGVs in a flexible manufacturing system where AGVs in the system are capable of carrying two or more loads. The load selection problem arises when an AGV stops at a pick-up queue and has to decide which part(s) should be picked up. Five heuristic rules that may be used to select the load to be carried were suggested and evaluated under a hypothetical flexible manufacturing system with the aid of computer simulation. The results revealed that the variable-route-part-priority (VP) rule and fixed-route-part-priority (FP) rule generated significantly higher throughput than their counterparts, while the ’pick-all-send-nearest’ (PN) rule outperformed the other rules in part flowtime and work-in-process level. The results also suggest that when the carrying capacity of the AGV increases, the performance differences among the rules also increase. This finding sustains the need to explore an efficient operation strategy of multiple-load AGVs in flexible manufacturing systems.     

Intelligent agent framework to determine the optimal conflict-free path for an automated guided vehicles system

Agent technology has been considered as an important approach for developing intelligent manufacturing systems. It offers a new way of thinking about many of the classical problems in manufacturing engineering. The conflict resolution of automated guided vehicles (AGVs) in a flexible manufacturing systems (FMS) environment is one such problem that comes under this category. This paper describe a multi-agent approach to the operational control of AGVs by integration of path generation, enumerating time-windows, searching interruptions, adjusting waiting time and taking decisions on the selection of routes. It presents an efficient algorithm and rules for finding a conflict-free shortest-time path for AGVs, which is applicable to a bi- and unidirectional flow path network. The concept of loop formation in a flow path network is introduced to deal with the parking of idle vehicles, without obstructing the path of moveable AGVs. The concept of loop formation at nodes reduces the timing-taking task of finding the dynamic positioning of idle AGVs in the network.     

Modelling battery constraints in discrete event automated guided vehicle simulations

This paper investigates a commonly omitted aspect of Automated Guided Vehicle (AGV) simulation—battery modelling. Battery usage is frequently overlooked in simulation for a variety of reasons. First, it is incorrectly believed to have minimal impact on system operation. Second, many analysts do not have an understanding of how batteries power AGVs. Third, battery analysis requires additional input information and varies for different AGV vendors. This paper contains several methods that can be used to account for the impact of various battery usage schemes on AGV simulations. These methods range from general philosophies to detailed model-specific coding examples.     

Route planning for automated guided vehicles in a manufacturing facility

Automated guided vehicles (AGVs) are widely used in manufacturing and transporting facilities for the movement of material from one location to another. Research in this area is directed toward the development of a path layout design and routing algorithms for movements of materials. The problem is to design a path layout and a routing algorithm that will route the AGVs along the bi-directional path so that the distance travelled will be minimized. This paper presents a bi-directional path flow layout and a routing algorithm that guarantee conflict-free, shortest-time routes for AGVs. Based on the path layout, a routing algorithm and sufficient, but necessary, conditions, mathematical relationships are developed among certain key parameters of vehicle and path. A high degree of concurrency is achieved in vehicle movement. Routing efficiency is analysed in terms of the distance travelled and the time required for AGVs to complete all pickup and drop-off jobs. Numerical results are presented to compare the performance of the proposed model. The research provides the foundation for a bi-directional path layout design and routing algorithms that will aid the designer to develop complicated path layouts.     

Logical reconfiguration of reconfigurable manufacturing systems with stream of variations modelling: a stochastic two-stage programming and shortest path model

Designing flexible manufacturing systems in general, and flexible material handling system in particular, is a complex problem, typically approached through several stages. Here the focus is on the conceptual design stage during which valid approximation-based methods are needed. The segmented flow topology (SFT) AGV systems were developed to facilitate control of complex automated material handling systems. This paper introduces a decomposition method, directly derived from timed Petri nets (TPN) theories, to calculate the expected utilization of AGVs (as servers of SFT systems) and to derive simple operational decision rules leading to maximum system productivity at steady state, for a given deterministic routeing of discrete material through the manufacturing system.     

Design and analysis of optimal material distribution policies in flexible manufacturing systems using a single AGV

Modern automated manufacturing processes employ Automated Guided Vehicle (AGV) for material handling, which serve several machine centres (MC) in a factory. Waiting time for resources such as AGVs are the longest elements that make up the Manufacturing Lead Time (MLT). Hence, optimal scheduling of AGVs can significantly help to increase the efficiency of the manufacturing process by minimizing the idle time of MCs waiting for the raw materials. In this paper, we will analyse the requirements for an optimal schedule and then provide a mathematical framework for an efficient schedule of material delivery by an AGV. The optimal schedule depends on several factors, such as the processing speeds of MCs, the speed and the material carrying capacity of the AGV, and system dependent overheads (such as loading and unloading time, machine set-up time, distance travelled, etc). A mathematical model is developed and then a strategy for optimal material distribution of the available raw material to the MCs is derived. With this model, the optimal number of MCs to be utilized will also be determined. Finally, the material delivery schedule employing multiple journeys to the MCs by the AGV will be carried out. Through rigorous analysis and simulation experiments, we shall show that such a delivery strategy will optimize the overall performance.     

Modelling of an automated guided vehicle system (AG VS) in a just-in-time (JIT) environment

Like other production systems, just-in-time (JIT) systems need to address the issue of material transport between workstations such as those served by automated guided vehicles (AGVs). Unlike other production systems, however, the JIT philosophy imposes strict requirements on inventory levels and supply-demand protocols which render conventional AGV delivery strategies ineffective and counter-productive. This paper describes the modelling of an AGV system (AGVS) in a JIT environment in a way that is consistent with JIT principles. The influence of a ‘JIT perspective’ is emphasized throughout the model by introducing threshold values for both input and output queues, performance measures that emphasize lower inventories in addition to transport efficiency, and a new dispatching rule that implements better inventory and transport control. The dispatching rule is shown to perform better in a JIT environment than previously developed AGV dispatching rules in both transport and logistic criteria.