A 5G campus network is a 5G network for the users affiliated with the campus organization, e.g., an industrial campus, covering a prescribed geographical area. A 5G campus network can operate as a so-called 5G non-standalone (NSA) network (which requires 4G Long-Term Evolution (LTE) spectrum access) or as a 5G standalone (SA) network (without 4G LTE spectrum access). 5G campus networks are envisioned to enable new use cases, which require cyclic delay-sensitive industrial communication, such as robot control. We design a rigorous testbed for measuring the one-way packet delays between a 5G end device via a radio access network (RAN) to a packet core with sub-microsecond precision as well as for measuring the packet core delay with nanosecond precision. With our testbed design, we conduct detailed measurements of the one-way download (downstream, i.e., core to end device) as well as one-way upload (upstream, i.e., end device to core) packet delays and losses for both 5G SA and 5G NSA hardware and network operation. We also measure the corresponding 5G SA and 5G NSA packet core processing delays for download and upload. We find that typically 95% of the SA download packet delays are in the range from 4–10 ms, indicating a fairly wide spread of the packet delays. Also, existing packet core implementations regularly incur packet processing latencies up to 0.4 ms, with outliers above one millisecond. Our measurement results inform the further development and refinement of 5G SA and 5G NSA campus networks for industrial use cases. We make the measurement data traces publicly available as the IEEE DataPort 5G Campus Networks: Measurement Traces dataset (DOI 10.21227/xe3c-e968).

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5G Campus Networks: A First Measurement Study

Visible Light Communication (VLC) is a short-range optical wireless communication technology that has been gaining attention due to its potential to offload heavy data traffic from the congested radio wireless spectrum. At the same time, wireless communications are becoming crucial to smart manufacturing within the scope of Industry 4.0. Industry 4.0 is a developing trend of high-speed data exchange in automation for manufacturing technologies and is referred to as the fourth industrial revolution. This trend requires fast, reliable, low-latency, and cost-effective data transmissions with fast synchronizations to ensure smooth operations for various processes. VLC is capable of providing reliable, low-latency, and secure connections that do not penetrate walls and is immune to electromagnetic interference. As such, this paper aims to show the potential of VLC for industrial wireless applications by examining the latest research work in VLC systems. This work also highlights and classifies challenges that might arise with the applicability of VLC and visible light positioning (VLP) systems in these settings. Given the previous work performed in these areas, and the major ongoing experimental projects looking into the use of VLC systems for industrial applications, the use of VLC and VLP systems for industrial applications shows promising potential.

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Visible Light Communications for Industrial Applications—Challenges and Potentials

Perception capability assumes significant importance for human–robot interaction. The forthcoming industrial environments will require a high level of automation to be flexible and adaptive enough to comply with the increasingly faster and low-cost market demands. Autonomous and collaborative robots able to adapt to varying and dynamic conditions of the environment, including the presence of human beings, will have an ever-greater role in this context. However, if the robot is not aware of the human position and intention, a shared workspace between robots and humans may decrease productivity and lead to human safety issues. This paper presents a survey on sensory equipment useful for human detection and action recognition in industrial environments. An overview of different sensors and perception techniques is presented. Various types of robotic systems commonly used in industry, such as fixed-base manipulators, collaborative robots, mobile robots and mobile manipulators, are considered, analyzing the most useful sensors and methods to perceive and react to the presence of human operators in industrial cooperative and collaborative applications. The paper also introduces two proofs of concept, developed by the authors for future collaborative robotic applications that benefit from enhanced capabilities of human perception and interaction. The first one concerns fixed-base collaborative robots, and proposes a solution for human safety in tasks requiring human collision avoidance or moving obstacles detection. The second one proposes a collaborative behavior implementable upon autonomous mobile robots, pursuing assigned tasks within an industrial space shared with human operators.

https://www.mdpi.com/1424-8220/21/5/1571/pdf

Human-Robot Perception in Industrial Environments: A Survey.

Mobile robots contributed significantly to the intelligent development of human society, and the motion-planning policy is critical for mobile robots. This paper reviews the methods based on motion-planning policy, especially the ones involving Deep Reinforcement Learning (DRL) in the unstructured environment. The conventional methods of DRL are categorized to value-based, policy-based and actor-critic-based algorithms, and the corresponding theories and applications are surveyed. Furthermore, the recently-emerged methods of DRL are also surveyed, especially the ones involving the imitation learning, meta-learning and multi-robot systems. According to the surveys, the potential research directions of motion-planning algorithms serving for mobile robots are enlightened.

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Motion Planning for Mobile Robots—Focusing on Deep Reinforcement Learning: A Systematic Review

The contemporary market creates a demand for continuous improvement of production, service, and management processes. Increasingly advanced IT technologies help designers to meet this demand, as they allow them to abandon classic design and design-testing methods in favor of techniques that do not require the use of real-life systems and thus significantly reduce the costs and time of implementing new solutions. This is particularly important when re-engineering production and logistics processes in existing production companies, where physical testing is often infeasible as it would require suspension of production for the testing period. In this article, we showed how the Digital Twin technology can be used to test the operating environment of an autonomous mobile robot (AMR). In particular, the concept of the Digital Twin was used to assess the correctness of the design assumptions adopted for the early phase of the implementation of an AMR vehicle in a company’s production hall. This was done by testing and improving the case of a selected intralogistics task in a potentially “problematic” part of the shop floor with narrow communication routes. Three test scenarios were analyzed. The results confirmed that the use of digital twins could accelerate the implementation of automated intralogistics systems and reduce its costs.

A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR’s) Operating Environment—A Case Study

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.

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

Dan Sun

Papers

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