Arbitrary Waveform Generation for IoT and Cyber Physical Systems Communication Networks Using C28x TMS320C2000 Digital Signal Processor

Oyekanlu, Emmanuel; Scoles, K.; Oladele, Paul

doi:10.1109/icait.2018.8686615

Cited by 1 publication

(1 citation statement)

References 8 publications

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“…Also, there is need for in-depth studies of the impact of synchronization inaccuracies on the QoS of TSN networks. Numerous IIoT, edge computing and smart manufacturing initiatives in FoFs will be executed using low-cost devices [327], [328], [329]. For such low-cost devices and sensors, especially those that are applied in large scale networks and in remote applications such as the remote control of AGVs shown in Figure 6, synchronization schemes employed by TSN networks may not be quite accurate [323].…”

Section: Reliable 5g Network Slicing and Network Resource Allocation For Agv/amr Applications -Open Challengesmentioning

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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Section: Reliable 5g Network Slicing and Network Resource Allocation For Agv/amr Applications -Open Challengesmentioning

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

View full text Add to dashboard Cite

show abstract

Arbitrary Waveform Generation for IoT and Cyber Physical Systems Communication Networks Using C28x TMS320C2000 Digital Signal Processor

Cited by 1 publication

References 8 publications

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

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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