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PurposeVirtual Reality (VR) based training is an efficient and promising digital tool. In the construction industry, studies have been conducted on the realisation of VR scenarios for construction operations, but the challenges lie in procedural scenario creation based on the knowledge and digital data of the construction project. The purpose of this paper is to address this issue.Design/methodology/approachA new system and interface allowing an automatic generation of a VR scenario for operating procedure (OP) based on 4D Building Information Modelling (BIM) and tasks authoring by the domain experts are presented. The first process, Automatic Scenario Generation, generates assembly tasks based on the BIM metadata. The second process, Expert Scene and Scenario Authoring, allows adding tasks that cannot be modeled in the BIM OP.FindingsWith the 4D BIM methodology, the 3D model of building as well as the 3D OPs contain a time dimension representing the construction phases or planning. The evolution in time of the construction site and the tools and procedures adapted to each construction project must be integrated in the VR simulations. Moreover, domain experts should have control over the scenario and should be able to author tasks assigned to the operator in training.Originality/valueA Unified Modeling Language based framework allows the reuse of BIM metadata to create the scene, VR interactions and the assembly procedure; the assembly procedure is embedded in the virtual environment considering the time (4D) in the construction of the building and is used as a training scenario for the operator; and the training scenario can be refined by adding operational knowledge, such as quality.

Augmented reality (AR) is more and more used in the industrial context for maintenance, assembly operation. However, owing to the evolution and maturity of the technology, it is still necessary to evaluate the usage and benefits of AR in an industrial context to go further than proof of concept. As such, this paper proposes an analysis of AR case study in the literature. Then, this paper presents a methodology for comparing AR and electronic document-based complex maintenance instructions considering tasks complexity and operator competency level. The main results show that the consultation duration of the AR tablet is 34% statistically faster than the PDF tablet. It also shows that error concerning similar objects is reduced thanks to AR. Moreover, the study specifically focuses on types of task that worth using AR. However, the study shows that usability of the AR device is less well rated than the PDF for “beginner–intermediate” operators. Finally, an in-depth analysis permits extracting recommendations of the different factors to take into account with industrial AR applications.

In the context of Industry 4.0, Cyber-Physical Production Systems (CPPS) and digital twins are key technologies for the management of huge amount of data generated by Industrial Internet of things (IIoT) devices. However, the interoperability and flexibility of different components is still an important challenge so as to integrate them in the process and fit all industrial specific needs. Thus, the main contribution of this paper is to propose a database architecture and a data model associated allowing multiple agents to work collaboratively and synchronously to perform high-level tasks. Therefore, it fulfils requirements and needs of Industry 4.0: interoperability, scalability, flexibility and resilience. The proposed architecture and model are implemented on a cyber-physical production system (CPPS) which is used in order to show and discuss several use cases examples.

This paper presents a methodology and the associated tool for enhancing decision making in shop floor layout using collaborative virtual reality, associated to real-time performance indicators in Industry 4.0. It first describes the collaborative architecture of the application. Subsequently, application features like: visualization at scale one (machines, industrial environment’s top view, product flow path), 3D model interaction (setting layout), physical process flow evaluation (spaghetti diagrams, Key Performance Indicators-KPI), testing multiple configurations (via save and load). Finally, paper illustrates possible usages and benefits of how VR tool helps improve ergonomics and safety; helps reduce deliberation time and bottlenecks through machine spatial footprint, visualization, scale one experience and referring KPIs.

Nowadays, humans and robots are working more closely together. This increases business productivity and product quality, leading to efficiency and growth. However, human and robot collaboration is rather static; robots move to a specific position then humans perform their tasks while being assisted by the robots. In order to get a dynamic collaboration, robots need to understand the human’s intention and learn to recognize the performed actions complementing therefore his capabilities and relieving him of arduous tasks. Consequently, there is a need for a human action recognition dataset for Machine Learning algorithms. Currently available depth-based and RGB+D+S based human action recognition datasets have a number of limitations, counting the lack of training samples along with distinct class labels, camera views, diversity of subjects and more importantly the absence of actual industrial human actions in an industrial environment. Actual action recognition datasets include simple daily, mutual, or healthrelated actions. Therefore, in this paper we introduce an RGB+ S dataset named “Industrial Human Action Recognition Dataset” (InHARD) from a real-world setting for industrial human action recognition with over 2 million frames, collected from 16 distinct subjects. This dataset contains 13 different industrial action classes and over 4800 action samples. The introduction of this dataset should allow us the study and development of various learning techniques for the task of human actions analysis inside industrial environments involving human robot collaborations.

Cybersickness (CS) is an affliction that limits the use of virtual reality (VR) applications. For decades, the measurement of cybersickness has presented one of the most challenges that have aroused the interest of VR research community. Having strong effects on users’ health, cybersickness causes several symptoms relating to different factors. In most cases, the literature studies for VR cybersickness evaluation adopt the questionnaire-based approaches. Some studies have focused on physiological and postural instability-based approaches, while others support the VR content. Despite the attention paid to define measurements for assessing cybersickness, there is still a need for a more complete evaluation model that allows measuring cybersickness in real time. This paper defines a conceptual model that integrates subjective and objective evaluation of CS in real time. The proposed model considers three CS factors (i.e. individual, software and hardware). The aim is to consider the heterogeneous findings (subjective and objective measures) related to the selected CS factors that define integrated indicators. The theoretical part of the model was initially validated by researchers who have comprehensive knowledge and skills in VR domain. As a research perspective, we intend to evaluate the proposed model through a practical case study.

One of Industry 4.0’s greatest challenges for companies is the digitization of their processes and the integration of new related technologies such as virtual reality (VR) and augmented reality (AR), which can be used for training purposes, design, or assistance during industrial operations. Moreover, recent results and industrial proofs of concept show that these technologies demonstrate critical advantages in the industry. Nevertheless, the authoring and editing process of virtual and augmented content remains time-consuming, especially in complex industrial scenarios. While the use of interactive virtual environments through virtual and augmented reality presents new possibilities for many domains, a wider adoption of VR/AR is possible only if the authoring process is simplified, allowing for more rapid development and configuration without the need for advanced IT skills. To meet this goal, this study presents a new framework: INTERVALES. First, framework architecture is proposed, along with its different modules; this study then shows that the framework can be updated by not only IT workers, but also other job experts. The UML data model is presented to format and simplify the authoring processes for both VR and AR. This model takes into account virtual and augmented environments, the possible interactions, and ease operations orchestration. Finally, this paper presents the implementation of an industrial use case composed of collaborative robotic (cobotic) and manual assembly workstations in VR and AR based on INTERVALES data.

L’essor des technologies numeriques, associe a la digitalisation des process industriels et aux evolutions de l’industrie 4.0, permettent l’introduction et l’usage d’interface homme/machine s’appuyant sur la realite augmentee pour assister les acteurs metiers dans un contexte industriel. Dans ce contexte, cet article traite des differents usages de la realite augmentee et de leur maturite, notamment pour des operations de maintenance, d’assemblage, de logistique ou encore de revue de conception. Pour cela, cet article s’interesse aux dispositifs de rendu en RA et aux caracteristiques associees a etudier en fonction du domaine applicatif. Enfin, les questions de creation des contenus, d’integration dans le systeme d’information et d’evaluation des usages sont abordees.

The adoption of digital technologies within industries and the evolution of technologies are opening new perspectives for using augmented reality (AR) and virtual reality (VR). Therefore, those technologies can facilitate the operators’ tasks working on complex industrial systems, either by bringing them some contextualised information in AR or by helping them with VR trainings. Thus they would improve their efficiency. However, integrating these new tools into existing processes of the company remains complex, due to the technologies and the data continuum needed, through the identification of use cases and the associated gains and by the diversity of actors and business experts involved in this process: the expert of the industrial system, the operator, the designer and the computer scientist.In order to develop those different industrial problematics, we first study the state of the art of scientific publications and existing technologies. Then, our research work has proposed a data modelling facilitating content authoring of augmented reality operations on industrial system. This work has also allowed to set up an experimental environment based on an educational production line and an augmented reality application developed thanks to that model.In a second part of this work, and in order to evaluate the efficiency of this technology, we have proposed a methodology allowing to evaluate augmented reality usage for maintenance, repair and operations on industrial systems according to performance, satisfaction and behavioural criteria. We analyse two case studies. They shows that contextualisation of information with augmented reality allows the operator to faster understand the task he needs to carry out than with paper instructions while reducing some kind of errors. Moreover we are proposing some guidelines in order to improve the augmented reality information efficiency. Besides, we are identifying which types of operation are improved with augmented reality. The work is also describing the rendering device influence on the use of augmented reality.Finally, and based on the augmented reality modelling, we are proposing an ontology allowing to unify content authoring of augmented and virtual reality so as to train or guide operator in their tasks. We are studying the use of this ontology for exploiting others data and company knowledge, as maintenance. This ontology is used for training scenarios in industrial environment and for guiding operator during their work.; L’adoption du numérique au sein des industries et les évolutions des technologies ouvrent de nouvelles perspectives d’usages de la réalité augmentée (RA) et de la réalité virtuelle (RV). Ainsi, ces technologies peuvent faciliter l’assistance des opérateurs travaillant sur des systèmes industriels complexes en utilisant la RA et permettre la mise en œuvre de formations en RV, améliorant donc leur efficience. Cependant, intégrer ces nouveaux outils aux processus existants de l’entreprise reste complexe, de par les aspects technologiques et le continuum de données à mettre en œuvre, de par l’identification des cas d’usages et des gains associés et de par la diversité d’acteurs et d’experts métiers à impliquer dans ce processus : l’expert du système industriel, l’opérateur, le concepteur et le développeur informatique.Afin d’aborder ces différentes problématiques industrielles et en se basant sur un état de l’art scientifique et technologique, nos travaux de recherche ont porté sur la proposition d’un modèle de données permettant de faciliter la création de contenu en réalité augmentée pour les opérations sur des systèmes industriels. Ces travaux ont également permis de mettre en place un environnement expérimental basé sur une chaîne de production didactique et une application créée grâce à ce modèle.Dans une seconde partie de ce travail, afin d’évaluer l’efficacité de cette technologie, nous avons mis en place une méthode permettant d’évaluer l’usage de la réalité augmentée pour la maintenance de systèmes industriels complexes selon des critères de performances et de satisfactions. L’analyse de deux études de cas montre que la contextualisation de l’information en réalité augmentée permet à l’opérateur de comprendre plus rapidement l’opération à effectuer qu’avec guide papier tout en réduisant certains types d’erreur. De plus, nous proposons des recommandations pour améliorer la pertinence de l’information fournie en réalité augmentée et identifions le type d’opération permettant d’obtenir un gain significatif, grâce à la réalité augmentée. Ces travaux s’intéressent également à l’influence et à la sélection des dispositifs de rendus.Enfin, en nous basant sur le modèle de données de RA, nous proposons une ontologie permettant d’unifier la création de contenu en réalité augmentée et virtuelle afin de former et guider un opérateur dans ses tâches. Nous étudions l’usage de cette ontologie pour exploiter d’autres données et connaissances de l’entreprise telles que celles liées à la maintenance. Cette ontologie est utilisée pour des scénarios de formation dans des environnements industriels et pour l’assistance sur des opérations.

International audience; Introducing the supervision system architecture of an agricultural robotic system enable the improved performance overcoming the complexity that current autonomous robots face due to the dynamic and unstructured agriculture environment. This requires the design of a human-robot interface. When designing a user interface several principles must be considered aiming to improve the usability of the user interface. This paper describes the design of the GUI web application and the coverage planner suitable for controlling the UV-Robot for typical coverage style greenhouse mildew treatment operations. The cross-platform user interface allows the farmer to specify their farm including fields, roads and docking stations, as well as controlling the whole operation. The contribution of this paper is to specify the design guidelines and the development of a user interface for a human-agricultural robot, in the case of UV treatment. Along with identifying the supervision system architecture and the communication control development, connecting the farmer, the UV-Robot and the cloud server associated.

Maintenance is a crucial point to improve productivity in industry whereas systems to be maintained have an increasing complexity. Augmented Reality (AR) can reduce maintenance process time and improve quality by giving virtual information and assistance to the operator during the procedure. In this paper, a workflow is firstly presented allowing a maintenance expert to author augmented reality maintenance procedures without computer skills. Then the AR maintenance application developed is described. Based on it, we present a case study which aims to compare maintenance efficiency with respect to the market available media support used, i.e. paper, video, AR tablet or AR Smart Glasses. A set of experiments involving 24 persons is described and analyzed. The results show that augmented reality maintenance reduce number of errors done by operator than with paper for the same duration of maintenance. A qualitative analysis shows that AR systems are well accepted by the users.

Augmented reality allows to add virtual object in real scene. It has an increasing interest last years since mobile device becomes performant and cheap. The augmented reality is used in different domains, like maintenance, training, education, entertainment or medicine. The demonstrator we show is focused on maintenance operations. A step by step process is presented to the operator in order to maintain an element of a system. Based on this demonstration, we will explain the modelling we propose allowing describing an entire maintenance process with augmented reality. Indeed it is still difficult creating augmented reality application without computer programming skills. The proposed model will allow to create an authoring tool — or to plug to an existing one — in order to create augmented reality process without deep computer programming skills.

Unrepeatered transmission of 160 25 GHz spaced channels at 10 Gbit/s over 380 km is demonstrated. The combination of recent advanced technologies, such as DWDM multiplexing/demultiplexing, large pump power, remote amplification, in-line filtering and FEC, allow this record transmission to be achieved.

Error-free unrepeatered transmission of 100 channels at 10 Gbit/s is demonstrated over 350 km. Enabling technologies are remote amplification, dual wavelength Raman pre-amplification and forward error correction leading to the longest error-free 1 Tbit/s unrepeatered transmission.

Raman amplification is a key technology for unrepeatered transmissions as it allows to widely increase both span length and optical bandwidth in a very simple manner. We review in this paper recent record demonstrations and installed systems where Raman amplification fulfills its role as a mean to reach very long repeaterless distances and to expand into new spectral areas.