Virtual Environments for Training: From Individual Learning to Collaboration with Humanoids

The next generation of virtual environments for training is oriented towards collaborative aspects. Therefore, we have decided to enhance our platform for virtual training environments, adding collaboration opportunities and integrating humanoids. In this paper we put forward a model of humanoid that suits both virtual humans and representations of real users, according to collaborative training activities. We suggest adaptations to the scenario model of our platform making it possible to write collaborative procedures. We introduce a mechanism of action selection made up of a global repartition and an individual choice. These models are currently being integrated and validated in GVT, a virtual training tool for maintenance of military equipments, developed in collaboration with the French company NEXTER-Group

Association of the PHACTR1/EDN1 genetic locus with spontaneous coronary artery dissection

Background: Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of acute coronary syndromes (ACS) afflicting predominantly younger to middle-aged women. Observational studies have reported a high prevalence of extracoronary vascular anomalies, especially fibromuscular dysplasia (FMD) and a low prevalence of coincidental cases of atherosclerosis. PHACTR1/EDN1 is a genetic risk locus for several vascular diseases, including FMD and coronary artery disease, with the putative causal noncoding variant at the rs9349379 locus acting as a potential enhancer for the endothelin-1 (EDN1) gene. Objectives: This study sought to test the association between the rs9349379 genotype and SCAD. Methods: Results from case control studies from France, United Kingdom, United States, and Australia were analyzed to test the association with SCAD risk, including age at first event, pregnancy-associated SCAD (P-SCAD), and recurrent SCAD. Results: The previously reported risk allele for FMD (rs9349379-A) was associated with a higher risk of SCAD in all studies. In a meta-analysis of 1,055 SCAD patients and 7,190 controls, the odds ratio (OR) was 1.67 (95% confidence interval [CI]: 1.50 to 1.86) per copy of rs9349379-A. In a subset of 491 SCAD patients, the OR estimate was found to be higher for the association with SCAD in patients without FMD (OR: 1.89; 95% CI: 1.53 to 2.33) than in SCAD cases with FMD (OR: 1.60; 95% CI: 1.28 to 1.99). There was no effect of genotype on age at first event, P-SCAD, or recurrence. Conclusions: The first genetic risk factor for SCAD was identified in the largest study conducted to date for this condition. This genetic link may contribute to the clinical overlap between SCAD and FMD

Contribution à la formation en réalité virtuelle : scénarios collaboratifs et intégration d'humains virtuels collaborant avec des utilisateurs réels

Industrial training is an emerging applicative domain for virtual reality. GVT (Generic Virtual Training) is a platform to create virtual environments for individual training on industrial procedures such as maintenance procedures. Nevertheless, industrial needs keep on evolving and a new request concerns training on collaborative procedures. In this thesis, we propose models to extend GVT possibilities to training on collaborative procedures where real users and virtual humans collaborate. We present an activity model for the actors which allows the dynamic substitution of a real user by a virtual human. This model makes an actor perform actions depending on his characteristics, on the scenario, on the environment and also on his partners' activity. We also propose an extension to the scenario language LORA in order to describe collaborative scenarios. Such a scenario describes the assignation of people to actions and integrates collaborative actions. The scenario has been simplified while making implicit some basic actions such as to take or to put back a tool. Finally, we present the action selection mechanism we have set up. Its aim is dual: to enable a virtual human to select an action to perform and to give a trainee some pedagogical advice about the best action to choose. This mechanism has two parts: a global module of action distribution in charge of determining the best candidate for each scenario action and one decisional module per actor. Indeed, an actor uses his collaborative profile (a set of behavioral rules) and the suggestion made by the action distribution module to choose the next action to perform. These models have been integrated to GVT in a prototype. In this thesis we present an applicative scenario which consists in collaboratively assembling a piece of furniture delivered in a kit.La formation industrielle est un domaine applicatif émergent pour la réalité virtuelle. GVT (Generic Virtual Training) est une plateforme de création d'environnements virtuels permettant une formation individuelle à des procédures industrielles de type maintenance. Cependant, les demandes industrielles évoluent et un nouveau besoin concerne la formation à des procédures collaboratives. Dans cette thèse nous proposons des modèles pour étendre les possibilités de GVT à la formation à des procédures collaboratives où des utilisateurs réels collaborent avec des humains virtuels. Nous présentons un modèle de l'activité des acteurs permettant de remplacer dynamiquement un apprenant par un humain virtuel. Ce modèle permet à un acteur de réaliser des actions en tenant compte de ses caractéristiques, du scénario, de l'environnement ainsi que de l'activité de ses partenaires. Nous proposons également une extension du langage de scénario LORA afin de décrire un scénario collaboratif. Un tel scénario décrit l'assignation des personnes aux actions et intègre des actions collaboratives. Le scénario a également été simplifié en rendant implicites des actions basiques comme la prise et la pose d'outils. Enfin, nous présentons le mécanisme de sélection d'action que nous avons mis en place et dont l'objectif est double : permettre à un humain virtuel de sélectionner une action à réaliser et donner des conseils à l'apprenant sur l'action à choisir. Il se compose de deux parties~: un module global de répartition des actions, chargé de déterminer le meilleur candidat pour chaque action du scénario, et des modules décisionnels dont dispose chaque acteur. Un acteur va ainsi se servir de son profil collaboratif (ensemble de règles de comportement) et de la suggestion du module de répartition pour choisir la prochaine action qu'il souhaiterait réaliser.Ces différents modèles ont été intégrés à GVT au sein d'un prototype. Dans cette thèse nous présentons un scénario applicatif réalisé dans GVT qui consiste à monter collaborativement un meuble livré en kit

Scenario sharing in a collaborative virtual environment for training

International audienceIn this paper, we describe a system used in the context of virtual training on collaborative maintenance procedures where the focus is on the learning of the industrial procedure rather than technical gestures. In existing collaborative virtual environments for training the distribution of scenario actions among actors is fixed: only one role can be associated with a given scenario action. In this paper, we propose to overcome this limitation and to add a mechanism to deal with this new flexibility. This mechanism is able to dynamically select the best actor for an action, based on various criteria, and to propose a distribution of actions among actors. We also propose to add collaborative profiles to virtual humans to guide them in order to select the next action to perform, possibly following the distribution suggestion. Trainees and virtual humans can then adapt their activities while respecting the reference procedure

Contribution à la formation en réalité virtuelle (Scénarios collaboratifs et intégration d'humains virtuels collaborant avec des utilisateurs réels)

GVT est un environnement virtuel permettant une formation individuelle à des procédures industrielles de type maintenance. Dans cette thèse nous proposons des modèles pour étendre les possibilités de GVT à la formation à des procédures collaboratives où des utilisateurs réels collaborent avec des humains virtuels. Nous présentons un modèle de l'activité d un acteur (réel ou virtuel) lui permettant de réaliser des actions en tenant compte de ses caractéristiques, du scénario, de l'environnement ainsi que de l'activité de ses partenaires. Nous proposons également une extension du langage de scénario LORA afin de décrire un scénario collaboratif. Un tel scénario décrit l'assignation des personnes aux actions et intègre des actions collaboratives. Enfin nous présentons le mécanisme de sélection d'action que nous avons mis en place et dont l'objectif est double : permettre à un humain virtuel de sélectionner une action à réaliser et donner des conseils à l'apprenant sur l'action à choisir.GVT is a virtual environment for individual training on industrial procedures such as maintenance procedures. In this thesis, we propose models to extend GVT possibilities to training on collaborative procedures where real users and virtual humans collaborate. We present an activity model for an actor (either real or virtual) which allows him to perform actions depending on his characteristics, on the scenario, on the environment and also on his partners' activity. We also propose an extension to the graphical scenario language LORA in order to describe a collaborative scenario. Such a scenario describes the assignation of people to actions and integrates some collaborative actions. Finally, we present the action selection mechanism we have set up. Its aim is dual: to allow a virtual human to select an action to perform and to give a pedagogical advice to a trainee about the best action to choose.RENNES-INSA (352382210) / SudocRENNES-INRIA Rennes Irisa (352382340) / SudocSudocFranceF

Humains virtuels et collaboration dans un environnement virtuel de formation

National audienceIndustrial needs keep on evolving and a new request is training on collaborative procedures. The GVT (Generic Virtual Training) platform to create virtual environments for training now allows trainees to train on collective procedures, by collaborating with other users or with virtual humans. New functionalities are available, such as: virtual humans with a collaborative profile which can be parameterized, who are interchangeable with real users; several types of collaboration, from synchronization to actions made by several persons; a collaborative scenario able to adapt itself to the context, and flexible relatively to the repartition of its actions between the actors; a mechanism able to determine at any time who is the best actor to realize a scenario action.Les besoins industriels en matière de formation évoluent et une nouvelle demande concerne la formation à des procédures collaboratives. La plateforme de création d'environnements virtuels de formation GVT (Generic Virtual Training) permet désormais à des apprenants de se former à des procédures collectives, en collaborant avec d'autres utilisateurs ou avec des humains virtuels. De nouvelles fonctionnalités sont proposées, notamment : des humains virtuels, disposant d'un profil collaboratif paramétrable, interchangeables avec des utilisateurs réels ; plusieurs types de collaborations possibles, de la synchronisation jusqu'aux actions à plusieurs ; un scénario collaboratif capable de s'adapter au contexte et flexible quant à la répartition de ses actions entre les acteurs ; un mécanisme capable de déterminer à tout moment quel est l'acteur le plus apte à réaliser une action du scénario

An operational VR platform for building Virtual Training Environments

International audienceWe present in this paper researches focused on specification and production of virtual training environments. The use of Virtual Environments (VE) for training is strongly stimulated by important needs of training on sensitive equipment. But the development of such applica- tions is generally done in new projects, where the reusability of existing developments is a major issue. We present here a platform of development, based on internal models that have been designed to achieve this reusability and standardization for the efficient development of new virtual environments.We defined a new generic model named STORM, used to describe reusable behaviors for 3D objects and reusable interactions between those objects or with humans. We also defined a scenario lan- guage named LORA, which allow non-computer scientists author various and complex sequences of tasks in a virtual scene. Based on those models, as an industrial validation with Nexter-Group, we have created 20 operational scenarios of maintenance virtual training on military equipments. We are also begining to create collaborative environments, where virtual and real humans have to collaborate to achieve their procedures

Adaptation in Collaborative Virtual Environments for Training

International audienceVirtual environments for training, especially collaborative ones, require adaptability in order to be used in various situations. In this paper, we classify the needs for adaptation into two levels. The first one concerns the application setting. The second one is a dynamic adaptation, at runtime. The models proposed in this paper fulfill these two levels of requirements. Virtual world, virtual humans’ behavior, scenario and application configuration can be adapted to a specific training situation. Moreover, an action selection mechanism enables actors to dynamically adapt their action scheduling to a situation. This situation is defined by a current context, past actions and a goal to achieve, namely a scenario. Finally we validate our models by presenting an illustrative scenario: the collaborative assembly of a piece of furniture

Music-Making and Musical Comprehension with Robotic Building Blocks

International audienceIn order to be used in various contexts of training, a desirable property for a virtual environment for training, especially a collaborative one, is adaptability. In this paper, we identify two levels of adaptability the environment should offer. The first level concerns the parametering of the components of the application, especially the scenario and the actors' behavior. The second level appears during the execution of the application where the actors should be able to adapt the scenario xecution to the context. The models proposed in this paper fully satisfy those requirements. The scenario, the virtual world, the actors and the training session can be parametrized. Moreover, an action selection mechanism enables the actors to dynamically choose an action to perform depending on both the current context and the past actions. Finally we validate our models by presenting an illustrative scenario within the GVT environment