Interacting with a multi AGV system

Cardarelli, Elena; Digani, Valerio; Secchi, Cristian; Fantuzzi, Cesare

doi:10.1109/iccp.2015.7312641

Cited by 9 publications

(10 citation statements)

References 24 publications

(16 reference statements)

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“…However, since AGVs might share industrial areas and routes with operators, a trustworthy and efficient collision avoidance mechanism should be enforced. This topic was tackled in the European Plug And Navigate (PAN)-Robots project [17][18][19]. In addition to an advanced sensing system, macroscopiclevel fleet and traffic management features were examined.…”

Section: Discussionmentioning

confidence: 99%

“…The Plug And Navigate (PAN)-Robots European project [17][18][19] aimed at improving the efficiency and autonomy of AGVs employed in industrial logistics facilities. AGVs used for the transportation of pallets in automated warehouses were considered.…”

Section: Related Workmentioning

confidence: 99%

“…The AGV Manager could also be an extension or be integrated with the WMS, ERP system or MES. A Graphical User Interface (GUI) could also be offered to the plant operators [18]. As depicted in Figure 1, the main Robot Controller service is responsible for all AGVs' mission and navigation control (i.e., pick-up/drop-off goods in given places, material/parts supply).…”

Section: Traffic Controllermentioning

confidence: 99%

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A Coloured Petri Net- and D* Lite-Based Traffic Controller for Automated Guided Vehicles

Mugarza

2021

Electronics

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Mobile robots, such as Automated Guided Vehicles (AGVs), are increasingly employed in automated manufacturing systems or automated warehouses. They are used for many kinds of applications, such as goods and material handling. These robots may also share industrial areas and routes with humans. Other industrial equipment (i.e., forklifts) could also obstruct the outlined routes. With this in mind, in this article, a coloured Petri net-based traffic controller is proposed for collision-free AGV navigation, in which other elements moving throughout the industrial area, such as humans, are also taken into account for the trajectory planning and obstacle avoidance. For the optimal path and collision-free trajectory planning and traffic control, the D* Lite algorithm was used. Moreover, a case study and an experimental validation of the suggested solution in an industrial shop floor are presented.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Traffic Controllermentioning

confidence: 99%

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A Coloured Petri Net- and D* Lite-Based Traffic Controller for Automated Guided Vehicles

Mugarza

2021

Electronics

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“…However, some weaknesses, such as the poor perception of pallets on racks and poor perception of dynamic objects such as walking humans were observed with the 3D mapping of the warehouse environment when laser scanners are used. Similar to researchers' approach in [195], researchers in [264] employed 3D representations of the factory floor to assist operators using Human Machine Interface (HMI) to interact effectively with AGV fleets [264]. The designed HMI allows operators to supply inputs that can influence the behavior of AGV fleets.…”

Section: G Applications and Use Casesmentioning

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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“…The use of the automated guided vehicle has increased significantly since their introduction. According to [5] Cardarelli, Sabattini, Digani, Secchi, and Fantuzzeti, human-machine interfaces facilitate the users to perform coordinated logistical activities within industrial environments. For example, PMD-cameras (Photonic Mixer Device camera) are typically used in sensing the obstacles within the path of an AGV.…”

Section: Automatic Guidancementioning

confidence: 99%

The Effect of Obstacle Design Architectures on Randomly Ranging AGVs in a Shared Workspace

Chowdhury¹,

Singh²,

Kluse³

et al. 2021

Adv. sci. technol. eng. syst. j.

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Interacting with a multi AGV system

Cited by 9 publications

References 24 publications

A Coloured Petri Net- and D* Lite-Based Traffic Controller for Automated Guided Vehicles

A Coloured Petri Net- and D* Lite-Based Traffic Controller for Automated Guided Vehicles

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

The Effect of Obstacle Design Architectures on Randomly Ranging AGVs in a Shared Workspace

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