Enabling Technologies for Autonomous Robotic Systems in Manufacturing

Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.

Building mm Wave on the Evolving C-V2X:mm Wave NR-V2X

Since the evolving standardization of cellular V2X(C-V2X)technologies is continuously developed by 3GPP,research on new radio(NR-V2X)has been on schedule by academic and industries.Though millimeter wave(mm Wave)frequency band is supposed to provide large transmission bandwidth,yet the development of mm Wave band in NR-V2X is still in preliminary stage.In this article,a comprehensive discussion of mm Wave NR-V2X is given covering trends,standardization landscape,and enabling technologies,aiming at tackling the challenge of channel modeling,directional channel access,beamforming and blockage management.The vision of mm Wave NR-V2X is to fully support the development of automated driving,holographic control display and improved in-car infotainment for the future.

Next Generation Network Enabled by ZTE's Softswitch Technology

Softswitch technology integrates the su-periorities of both an intelligence net-work and the Internet, which embodiesits maturity and advancement. With ahierarchical network model, it effectivelysolves problems of evolution and convergenceof current communication networks. It also fol-

Towards Intelligent Reflecting Surface Empowered 6G Terahertz Communications: A Survey

Terahertz(THz)communications have been widely envisioned as a promising enabler to provide adequate bandwidth and achieve ultra-high data rates for sixth generation(6G)wireless networks.In order to mitigate blockage vulnerability caused by serious propagation attenuation and poor diffraction of THz waves,an intelligent reflecting surface(IRS),which manipulates the propagation of incident electromagnetic waves in a programmable manner by adjusting the phase shifts of passive reflecting elements,is proposed to create smart radio environments,improve spectrum efficiency and enhance coverage capability.Firstly,some prospective application scenarios driven by the IRS empowered THz communications are introduced,including wireless mobile communications,secure communications,unmanned aerial vehicle(UAV)scenario,mobile edge computing(MEC)scenario and THz localization scenario.Then,we discuss the enabling technologies employed by the IRS empowered THz system,involving hardware design,channel estimation,capacity optimization,beam control,resource allocation and robustness design.Moreover,the arising challenges and open problems encountered in the future IRS empowered THz communications are also highlighted.Concretely,these emerging problems possibly originate from channel modeling,new material exploration,experimental IRS testbeds and intensive deployment.Ultimately,the combination of THz communications and IRS is capable of accelerating the development of 6G wireless networks.

Enabling Technologies in the Problem Solving Environment HEDP

Enabling technologies are those technologies preparing input data,analyzing output data and facilitating the whole processes for numerical simulations.This paper outlines current enabling technologies for large-scale multidisciplinary simulations used in the High End Digital Prototyping(HEDP)system,a problem solving environment equipped with capability of mesh generation and large-scale visualization.A problem solving environment is a computer system that provides all the computational facilities necessary to solve a target class of problems.Mesh generation continues to be the pacing technology for a practical numerical analysis,which is essential to yielding an accurate and efficient solution.Large-scale visualization maps the massive data to some kinds of scenes interactively,which can be realized through a tiled display wall system with distributed visualization capability.HEDP is designed for large-scale andmultidisciplinary simulations,and there are four categories of modules involved,namely pre-processing module,computing module,post-processing module,and platform control module.All these modules are coupled through a software bus,which makes the modules integrated seamlessly.Detailed design principles and applications of the HEDP environment are addressed in this paper.

Survey of Safety Management Approaches to Unmanned Aerial Vehicles and Enabling Technologies

Unmanned aerial vehicle(UAV)has a rapid development over the last decade.However,an increasing number of severe flight collision events caused by explosive growth of UAV have drawn widespread concern.It is an important issue to investigate safety management approaches of UAVs to ensure safe and efficient operation.In this paper,we present a comprehensive overview of safety management approaches in large,middle and small scales.In large-scale safety management,path-planning problem is a crucial issue to ensure safety and ordered operation of UAVs globally.In middle-scale safety management,it is an important issue to study the conflict detection and resolution methods.And in small-scale safety management,real-time collision avoidance is the last line of ensuring safety.Moreover,a UAV can be regarded as a terminal device connected through communication and information network.Therefore,the enabling technologies,such as sensing,command and control communication,and collaborative decision-making control technology,have been studied in the last.

The Practical Challenges and Ecological Construction of the Lifelong Learning System in the Digital Era

At present,intelligent digital technology is irreversibly influencing all levels of the education field.The construction of an education system serving lifelong learning has also become an essential field of digital transformation.In the face of the impact of marketization,aging,and networking,as well as the update and iteration of intelligent digital technology,the construction of the lifelong learning system not only needs to realize the transformation with the help of digital technology but also needs to clarify the internal correlation of transformation goals,computing power support,multiple collaboration,and learning evaluation from the framework structure.At the same time,it is necessary to realize that the penetration of technology into lifelong learning may cause the misunderstanding of technology supremacy and the trap of tool rationality.Therefore,technological empowerment and enablement can accelerate the digital transformation of the lifelong learning system and coordinate with community education,elderly education,vocational education,higher education,and other fields to construct an integrated environment.Additionally,being critical issues requiring attention from society,they are also vital ways to overcome the above dis advantages,promote interactions between communities,governments,and professional education organizations,and improve the digital and intelligent learning environment.

Preface

Complex networks are ubiquitous in our lives. Representative examples are the Internet, social networks, biological networks, E-commerce networks, electrical power grids, and larger-scale engineering systems. It is well known that the Internet has been a powerful engine for our societal evolution and technological innovation. Nowadays, network science and engineering faces fundamental challenges, such as understanding the complexity of various large-scale networks, developing new architectures and exploiting new substrates, and enabling new applications and new economics. To a better future, the complex networks in our lives will need to be better： more accessible, more reliable, more predictable, and more secure.