Comprehensive Review of the Dispatching, Scheduling and Routing of AGVs

Vivaldini, Kelen Cristiane Teixeira; Rocha, Luís F.; Becker, Marcelo; Moreira, António Paulo

doi:10.1007/978-3-319-10380-8_48

Cited by 21 publications

(11 citation statements)

References 37 publications

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“…Both the hardware and the algorithms for automated guided vehicles (AGV) are much more advanced than their modular counterparts. The following overview publications describe state-of-the-art AGV routing algorithms: [9]- [11], [24]. As with the modular conveying systems, we will only focus on algorithms from the class of "Time-window-based Route Reservation."…”

Section: B Automated Guided Vehiclesmentioning

confidence: 99%

Decentralized Routing Algorithm with Physical Time Windows for Modular Conveyors

Sohrt¹,

Overmeyer²

2019

Preprint

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We describe a decentralized routing algorithm with physical time windows for modular conveying systems. Existing routing algorithms for modular conveyors are already capable of bi-directional conveying while avoiding conflicts such as collisions, deadlocks, livelocks and starvation effects. In addition to avoiding conflicts, routing algorithms must also select routes that reduce the travel time. No existing algorithm for modular conveyors bases this decision on the expected physical lead time, even though physical lead time directly affects the system throughput. In this publication, we present an algorithm that uses the physical lead time to select routes while avoiding conflicts.

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Section: B Automated Guided Vehiclesmentioning

confidence: 99%

Decentralized Routing Algorithm with Physical Time Windows for Modular Conveyors

Sohrt¹,

Overmeyer²

2019

Preprint

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“…Furthermore, AGVs use a map to follow the routes which are predetermined to travel from first station origin to last station destination (19); (20), i.e. the input data do not change through the path execution (21). This route is recognized between two stations or sites where AGV is moving from site A to site B in fixed path.…”

Section: Automated Guided Vehicles Routingsmentioning

confidence: 99%

“…Meanwhile, the scheduling are divided into two main factors, a predictive mechanism that calculated the planned start and execution time of labor operations and a interacting mechanism that monitors the progress of the schedule and transact with unpredicted actions (cancellations, date changes, breakdowns, etc.) (21). In fact, the scheduling decision might include choosing a vehicle among some idling vehicles or choosing one load between wholly loads to be transported.…”

Section: Agv Schedulingmentioning

confidence: 99%

Automated Guided Vehicle Routing: Static, Dynamic and Free range

Hasan¹,

Abidin²,

Said³

2019

IJEAT

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Nowadays, automated guided vehicles (AGV) play very important role in modern factory automations. The AGV systems provide efficient routing for material flow and distribution among workstations at the exact time and place. Routing of AGV is the process of determining routes to fulfill their respective transport jobs. The routing problem of AGV in production system can be studied as a shortest path problem on a transfer network. It aims to find the shortest path between two vertices or nods. Most transport systems using AGV are centrally controlled and use static routing (pre-defined routes), which follows fixed line. Instead of using fixed path, dynamic routing for AGV can be used to add a high flexibility to the system. To accommodate the increased flexibility and reduced time, new operational controllers using Labview software must be able to adapt to small deviations. In this paper, routing of AGV, different AGV shortest path algorithms such as Dijkstra algorithm, A-star algorithm, Short Path Problem with Time Window (SPPTW), hybrid partial swarm optimization and genetic algorithm PSOGA are discussed with highlights of their main differences and comparison between them. AGV Scheduling is presented. In addition, the controller developed within Labview environment directs an AGV in real time using local position system are achieved.

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“…Applications, design and use cases [22], [23], [24] Review of Autonomous Industrial Mobile Manipulation (AIMM) system use cases as mobile manufacturing assistants in the industry. AGV material handling processes.…”

Section: Introductionmentioning

confidence: 99%

A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications

et al. 2020

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In industrial environments, over several decades, Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) have served to improve efficiencies of intralogistics and material handling tasks. However, for system integrators, the choice and effective deployment of improved, suitable and reliable communication and control technologies for these unmanned vehicles remains a very challenging task. Specifics of communication for AGVs and AMRs imposes stringent performance requirements on latency and reliability of communication links which many existing wireless technologies struggle to satisfy. In this paper, a review of latest AGVs and AMRs research results in the past decade is presented. The review encompasses results from different past and present research domains of AGVs. In addition, performance requirements of communication networks in terms of their latencies and reliabilities when they are deployed for AGVs and AMRs coordination, control and fleet management in smart manufacturing environments are discussed. Integration challenges and limitations of present state-of-the-art AGV and AMR technologies when those technologies are used for facilitating AGV-based smart manufacturing and factory of the future applications are also thoroughly discussed. The paper also present a thorough discussion of areas in need of further research regarding the application of 5G networks for AGVs and AMRs fleet management in smart manufacturing environments. In addition, novel integration ideas by which tactile Internet, 5G network slicing and virtual reality applications can be used to facilitate AGV and AMR based factory of the future (FoF) and smart manufacturing applications were motivated.INDEX TERMS Intelligent factory, factory of the future, 5G, smart manufacturing, industry 4.0, autonomous industrial equipment, AGV, AMR, tactile Internet, virtual reality, lean manufacturing.

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Comprehensive Review of the Dispatching, Scheduling and Routing of AGVs

Cited by 21 publications

References 37 publications

Decentralized Routing Algorithm with Physical Time Windows for Modular Conveyors

Decentralized Routing Algorithm with Physical Time Windows for Modular Conveyors

Automated Guided Vehicle Routing: Static, Dynamic and Free range

A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications

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