12-12-2012, 03:19 PM
CONTROL CLASSIFICATION OF AUTOMATED GUIDED VEHICLE SYSTEMS
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ABSTRACT
An automated guided vehicle or automatic guided vehicle (AGV) is a mobile robot that follows markers or wires in the floor, or uses vision or lasers. They are most often used in industrial applications to move materials around a manufacturing facility or a warehouse. Application of the automatic guided vehicle has broadened during the late 20th century and they are no longer restricted to industrial environments. Automated guided vehicle systems (AGVS) are widely used for transporting material in manufacturing and warehousing applications. These systems offer many advantages over other forms of material transport. However, the design of these systems is complex due to the interrelated decisions that must be made and the large number of system design alternatives that are available. In particular, the design of the AGVS control system can be quite challenging, and it can dramatically affect the system cost and performance. This paper presents a classification of automated guided vehicle systems developed from a control perspective. This classification is demonstrated on several example systems from the literature.
INTRODUCTION
Automated guided vehicle systems (AGVS) are commonly used for transporting material within a manufacturing, warehousing, or distribution system. These systems provide for asynchronous movement of material through the system and are used in a wide variety of applications. They offer many advantages relative to other types of material handling systems, including reliable, automatic operation, flexibility to changes in the material handling requirements, improved positioning accuracy, reduced handling damage, easily expandable layout and system capacity, and automated interfaces with other systems (Miller, 1987). The design of AGVS, however, can be very complicated.
A number of interrelated decisions must be made including determining the guide path layout and characteristics, the number and type of vehicles, the location, type, and buffer capacities of pickup/deposit stations, the operating procedures (e.g., vehicle dispatching and routing), the type of communications, and the type and characteristics of the control system (e.g., centralized, decentralized, zone or distributed, etc.) (Bakkalbasi and McGinnis, 1988; Bohlander and Heider, 1988). There has been considerable research into these different aspects of AGVS design (e.g., see Maxwell and Muckstadt, 1982; Gaskins and Tanchoco, 1987; Kouvelis et al., 1992; Sinriech and Tanchoco, 1991 and 1992; Egbelu, 1987; Tanchoco et al., 1987; Kiran and Tansel, 1989; Goetz and Egbelu, 1990).
AGVS CONTROLLER STRUCTURE
In automated or semi-automated manufacturing systems, the AGVS controller is an integral part of the shop floor control system. The shop floor control system is responsible for routing products through the individual processing stations and interacting with the shop floor equipment and operators to affect production. The AGVS’s role is to facilitate the transport of parts, tools, fixtures, etc., between individual processing centers as specified by the shop floor control system.
Joshi et al. (1990) and Smith et al. (1992) describe a hierarchical shop floor control system in which the control functions have been partitioned into planning, scheduling, and execution functions. According to this architecture, planning is responsible for determining which tasks the control system should perform. This responsibility includes decomposing tasks into smaller sub-tasks and selecting the most appropriate task when alternatives exist. For example, in the case where multiple machines are available to process a given part, the planning function will select a specific machine. Scheduling then sequences and/or assigns start/end times to the planned tasks. Finally, execution interacts with the lower control levels or the physical equipment to perform each task. The rationale of this partitioning is that the execution function depends only on the configuration of the physical system, whereas the planning and scheduling functions also depend on the production requirements. In a flexible manufacturing system, the production requirements change much more frequently than the physical system configuration. Consequently, the planning and scheduling functions can change as required by the production requirements, and the execution functions will remain unaffected
Detailed Schematic of AGVS Controller
Conflict in automated guided vehicle routing is said to occur when two or more vehicles are temporarily delayed if they are: (1) traveling along the same guidepath but at different speeds, or (2) arrive at the same intersection from different guidepath segments. The AGVSC must be able to resolve the conflict. Researchers have proposed several rules for resolving conflict at intersections in unidirectional, single lane/aisle, guidepath networks, such as: allowing departure of vehicles from an intersection on a first-come-first-served basis, restricting the first-come-first-served rule to vehicles transferring to the same path segment, prioritizing tasks and allowing departure based on these priorities, etc. (Egbelu and Tanchoco, 1982 and 1984). Also, Taghaboni and Tanchoco (1988) present a number of similar rules for unidirectional, two lanes/aisle guidepath networks.
AGVS CLASSIFICATION
The purpose of the classification scheme described in this paper is to identify design alternatives of the AGVS that impact the controller design. This classification shows the impact each of these decisions has on the controller design. Based on the controller structure described in the previous section, the classification identifies the controller functionalities required for a particular system design. However, these functionalities can be implemented using a variety of different control system structures.
The classification system has three basic levels as shown below.
. Guidepath Determination
AGVS guidepaths are determined in one of two ways: static a priori determination or dynamic real-time determination. In a static guidepath system, the vehicles use a set of predetermined paths between possible origins and destinations. The vehicles can use a variety of guidance mechanisms, such as floor embedded guide wires, chemical/optical sensor stripes, dead reckoning and position updating using targets or beacons based on a software map of the paths, etc. Dynamic real-time systems use completely autonomous vehicles that are capable of determining a path using obstacle detection and avoidance systems. With dynamic paths, the vehicle is given the destination, which is a location that it knows about, perhaps specified relative to some world coordinate system. The vehicle then determines the path from its current position to the destination using its internal navigation scheme. Note that a virtual guidepath system (Taghaboni and Tanchoco, 1988; Gaskins et al., 1989), in which there is no physical guidepath, but the supervisory controller determines the specific path from a set of fixed paths in a database, is considered a static guidepath system. In this case, the controller function is the same, although the vehicle navigation system changes significantly.
Vehicle Capacity
AGVs can be classified as either single load or multiple load vehicles, depending on the number of loads that the vehicle can simultaneously carry. For our purposes, a load consists of a single “unit” carried by the vehicle from an origin to a destination. This unit may contain a number of distinct parts of the same or different types, e.g., assembly kits contained in a tote, but are considered a single load as long as all of the parts have the same origin and destination and the vehicle handles the tote as a unit. For AGVS with multiple vehicle types, the system will be considered a multiple load system if any of the vehicles are multiple load vehicles. The distinction for the control system lies primarily in the planning function.
In a single load system, an idle, empty vehicle is selected for a task (i.e., assigned a load to deliver). The vehicle then travels from its current position to the pickup station to obtain the load and then travels to the destination station to drop off the load. Once the vehicle is assigned the task, it is not interrupted with another task assignment (although this would be possible anytime before the vehicle has reached the pickup station). The planning function must dispatch the vehicle (assign it to a task) and determine the route for the vehicle from its current location to the task origin and then to the task destination.
Vehicle Addressing Mechanism
AGVS can be classified as direct or indirect address systems, depending on the nature of the system operation. In an indirect address system, each vehicle visits the load/unload stations in a fixed sequence, similar to a city bus service. In this case, the routes for each vehicle are determined in advance as part of the system design and are, therefore, not part of the controller planning function. In addition, dispatching in an indirect address system is straightforward. Since the vehicle visits the stations in a prescribed order, it picks up and drops off loads as it comes to the appropriate station. The only complication is if the controller can have the vehicle “wait” at a particular station for a load to arrive.
With indirect systems, the route for each vehicle may not include every station in the system. That is, the stations are partitioned such that a vehicle serves some subset of the stations. This situation introduces a different type of planning problem, namely, how to “route” a load through the system. It may occur that a load’s origin is served by one vehicle and a load’s destination is served by a different vehicle. In this case, the load must be transferred from one vehicle to another, much as people transfer between buses. Depending on the configuration of the system, the load may be handled by several vehicles before reaching its destination. In addition, there may be alternative “routes” for the load to take from its origin to its destination.
CONCLUSIONS
This paper presents a classification scheme for automated guided vehicle systems. This scheme is developed from a system control perspective. The paper provides a discussion of the functionalities required of a generic AGVS controller. The classification scheme is then developed based on the impact the AGVS design alternatives have on the control system. This classification scheme is illustrated with a number of examples from the literature. The scheme is useful as a structured method for understanding the impact of design decisions on the control system. It provides a mechanism for organizing the academic literature on AGVS and comparing the application domains of different techniques.