Abstract As virtual reality (VR) simulators become increasingly central to technical training, realistic haptic feedback is often assumed to enhance user experience, skill acquisition, and transfer to real-world tasks. This study investigates the impact of haptic feedback on basic technical motor skill training in VR, focusing on early-stage skills involving bimanual coordination, fine motor control, and precise tool-mediated object placement under visual and temporal constraints, with limited force modulation requirements. An immersive simulator implementing a bimanual “Ring Transfer” task was developed, requiring participants to precisely grasp and transfer small objects using two tools under visual guidance and timing constraints, with minimal force modulation. A closely matched physical setup replicating workspace dimensions, tool geometry, and interaction mechanics was used to assess skill transfer. Twenty-four novice participants were assigned to three groups: haptic (HC), no-haptic (NC), and control (CC), consistent with an a priori power analysis. The HC and NC groups completed nine training sessions over two weeks, followed by post-test and delayed retention evaluations conducted one week later. Performance was measured using task completion time and error rate, and user experience was assessed using the System Usability Scale (SUS) and a validated Presence Questionnaire. Results show that the NC group initially outperformed the HC group, likely due to increased cognitive and sensorimotor demands associated with adapting to force feedback. However, the latter demonstrated greater performance improvement over time. Both groups reported high usability, while the HC group reported significantly higher scores on the haptics dimension of the Presence Questionnaire. In the physical post-test, both trained groups significantly outperformed the control group, confirming effective transfer from VR to real-world performance. However, no significant difference was found between the HC and NC groups, indicating that the increased perceived realism associated with haptic feedback did not translate into measurable performance gains for this task. These findings highlight a task-dependent role of haptic feedback. In this study, basic tasks are characterized by a predominant reliance on visual guidance and spatial precision, with limited requirements for force control or tactile discrimination. For such tasks, visual information alone may be sufficient to support skill transfer. This suggests that the benefits of haptics in VR training depend on task demands, particularly the extent to which force control and tactile cues are required, whereas tasks involving significant force modulation or interaction with deformable objects may benefit more from haptic feedback.

With the increasing use of immersive simulators in surgical training, there is an emerging emphasis on providing realistic haptic feedback. Although haptic feedback is recognized as necessary for surgical skill acquisition, its role in transferring those skills to real-life situations still needs to be explored. Our study aims to investigate the impact of haptic feedback on basic microsurgery skill acquisition, transfer, and retention, as well as on the user experience during VR training. An immersive simulator was developed to practice a microgrid task under magnification with and without haptic feedback. A similar physical setup with a binocular microscope was also designed to measure skills transfer to the real world. Thirty-three volunteers ($N=33$) were randomly divided into three participant groups: the haptic feedback group (HG), the no-haptic feedback group (NG), and the control group (CG). All participants performed the task on the physical setup during the pre-post-retention tests. After the pre-test, the first two groups performed six training trials on the immersive simulator, with the HG group receiving haptic feedback while performing the task. The control group did not receive any training. The results show that the HG and NG groups significantly improved their learning curve during training, with no significant differences between them. On the Other hand, the haptic feedback led to significantly higher usability and possibility of examination scores than those without haptic feedback. Finally, all the groups improved their time performance on the physical simulator. In addition, the haptic group participants showed a more significant gain in performance in terms of accuracy and error rates. These findings confirm the effectiveness of immersive environments combined with haptic feedback as a valuable training tool, facilitating the transfer of technical skills to realworld applications. Moreover, the results indicate that haptic feedback can also improve the user experience in immersive surgical simulators.

We propose a novel object detection framework tailored for mixed reality (MR), combining a customizable synthetic dataset with a lightweight attention-enhanced detection model. Our dataset generation pipeline synthesizes planetary and telescope foregrounds with hybrid real-synthetic backgrounds, enabling robust learning across variable lighting and occlusion scenarios—challenges common in educational MR environments. At the core of our architecture is the Dual Focus Multiscale Attention (DFMA) module, which simultaneously refines spatial and channel-wise features at multiple scales. Integrated into a YOLO-based (You Only Look Once) backbone and FPN, DFMA significantly improves feature discrimination while preserving real-time efficiency. On MS COCO our model improves mean Average Precision (mAP) across Intersection over Union (IoU) thresholds from 0.5 to 0.95 ([email protected]:0.95) over state-of-the-art nano detectors from 39.3% to 41.3% (± 2%) at only +6% params and +3% GFLOPs, with a notable reduction in false positives on visually similar, low-textured objects. We further demonstrate real-time deployment in a Unity-based MR application, highlighting the system's effectiveness in immersive astronomy-focused educational scenarios. Our results underscore the potential of synthetic data and multiscale attention to bridge accuracy, speed, and realism in next generation MR systems.

This study investigates the impact of two immersive debriefing strategies on learning outcomes in a virtual reality (VR) simulation focused on mobile cybersecurity. The simulation highlights everyday mistakes to raise awareness of risky behaviors in public settings. We developed and evaluated an immersive debriefing system that enables participants to review their performance and re-engage with the scenario through a redo phase. This redo was implemented in two formats: a full scenario redo (F-REDO) and a segmented redo targeting specific moments (S-REDO). We found that both redo formats were equally effective in learning outcomes and user satisfaction, using a mixed-methods approach combining standardized questionnaires (motivation, cognitive load, usability, knowledge retention) and qualitative trainer feedback. However, S-REDO demonstrated greater time efficiency without increasing cognitive load and was perceived by the trainer as more engaging and pedagogically relevant. These results support the integration of personalized, interactive debriefing tools in VR learning environments, particularly in domains requiring targeted remediation and critical decision-making. Abstract Abstract

We introduce a compact video-classification pipeline for real-time dynamic hand-gesture recognition in mixed-reality (MR) settings. The network marries a MobileNetV3 backbone with two purpose-built temporal components: (1) a Gated Discriminative Temporal Shift Module (G-DiTSM) that inserts first-order motion differences and learns channel-wise gates to fuse them adaptively, and (2) a lightweight Depth-Efficient Channel Attention (DepthECA) block that recalibrates spatial features on the fly. Operating on eight sparsely sampled frames per clip (Temporal Segment Network paradigm), the resulting model contains 2.65 M parameters and requires only 0.084 GFLOPs per inference. Evaluated on the RGB-only 20BN Jester benchmark (148k clips spanning 27 gesture classes) recorded from front-facing viewpoints. The system reaches 95.34% Top-1 and 99.80% Top-5 accuracy, surpassing recent 3D CNNs and transformer baselines while being an order of magnitude lighter. Ablations confirm that DepthECA and G-DiTSM provide complementary gains (+18.78% and +0.93% Top-1, respectively, over the MobileNetV3 baseline). Because all components are plug-and-play and introduce minimal overhead, the architecture is well suited to the tight latency and power budgets of standalone MR headsets, paving the way for natural grab, rotate, and command interactions using only on-board RGB cameras

In the early stages of learning a technical skill, trainees require guidance from a mentor through augmented feedback to develop higher expertise. However, the impact of such feedback and the different modalities used to communicate it remain underexplored in immersive virtual environments (IVE). This paper presents a study in which 27 participants were divided into three groups to learn a tool manipulation trajectory in an IVE. Two experimental groups received guidance from an expert using visual and/or haptic augmented feedback, while the control group received no feedback. The results indicate that both experimental groups showed significantly greater improvement in tool trajectory performance than the control group from pre- to post-test, with no significant differences between them. Analysis of their learning curves revealed similar performance improvements in tool trajectory across trials, outperforming the control group. Additionally, the visual-haptic feedback condition was linked to lower task load in three out of six dimensions of the NASA-TLX and a higher perceived interdependence with the expert's actions. These findings suggest that augmented feedback from an expert enhances the learning of tool manipulation skills. Although adding haptic feedback did not lead to better learning outcomes compared to visual feedback alone, it did enhance the overall user experience. These results offer valuable insights for designing IVEs that support mentor-trainee interactions through augmented feedback.

Real-time object detection in indoor settings is a challenging area of computer vision, faced with unique obstacles such as variable lighting and complex backgrounds. This field holds significant potential to revolutionize applications like augmented and mixed realities by enabling more seamless interactions between digital content and the physical world. However, the scarcity of research specifically fitted to the intricacies of indoor environments has highlighted a clear gap in the literature. To address this, our study delves into the evaluation of existing datasets and computational models, leading to the creation of a refined dataset. This new dataset is derived from OpenImages v7[14], focusing exclusively on 32 indoor categories selected for their relevance to real-world applications. Alongside this, we present an adaptation of a CNN detection model, incorporating an attention mechanism to enhance the model’s ability to discern and prioritize critical features within cluttered indoor scenes. Our findings demonstrate that this approach is not just competitive to existing state-of-the-art models in accuracy and speed but also opens new avenues for research and application in the field of real-time indoor object detection.

International audience

With the mentoring model, a mentee can learn technical skills under the supervision of more experienced peers who demonstrate their knowledge through several communication modalities. Supporting the mentoring model within shared immersive training simulators holds promise in enhancing mentor-mentee interactions and learning outcomes in a safe environment. However, efficient communication within these spaces remains an open issue. This work presents a user study that explores the combination of communication modalities (verbal-visual, verbal-haptic, visual-haptic, and verbal-visual-haptic) to convey instructions to learners on the amplitude of movements to perform during a tool-handling task in an immersive environment. The study aims to examine the impact of the four modality combinations on performance (speed and accuracy of movement replication), mental workload, and participants’ user experience. The results show that participants achieved higher accuracy with the visual-haptic and verbal-visual-haptic conditions. Moreover, they performed the movements faster, and their movement trajectories were closer to the reference trajectories in the visual-haptic condition. Finally, the most preferred verbal-visual-haptic combination enhanced the users’ sense of presence, co-presence, social presence, and learning experience. No impact on the mental workload was observed. These results suggest that combining haptic and visual modalities is the best suited for enhancing learners’ performance. Adding the verbal modality can also improve the user experience in the immersive learning environment. These findings contribute to improving the design of immersive collaborative systems and pave the way for exploring novel avenues of research into the efficacy of multimodal communication for enhancing the mentoring-based acquisition of technical skills in VR. These tools hold promise for diverse applications, including medical simulation.

Simulation and debriefing are two essential and inseparable phases of virtual reality training. With the widespread adoption of these training tools, it is crucial to define the best pedagogical approaches for trainers and learners to maximize their effectiveness. However, despite their educational benefits, virtual reality-specific debriefing methods remain underexplored in research. This article proposes an architecture and interface for an all-in-one immersive debriefing module that is adaptable to different types of training, including a complete system for recording, replaying, and redoing actions. A study with 36 participants compared this immersive debriefing system with traditional discussion-based and video-supported debriefing. Participants were divided into three groups to evaluate the effectiveness of each method. The results showed no significant differences between these debriefing methods across several criteria, such as satisfaction, motivation, or information retention. Immersive debriefing is as usable and retentive as traditional or video debriefing in this context. The next step will be to evaluate the redo system in other training courses involving more dynamic scenarios.

In this paper, a custom Single Shot Multi-box Detector (SSD) [1] is proposed for object detection on difficult scenes. The fruit 360 dataset [2], with low-textured images of different fruits and vegetables, is used as a training and validation data set. The purpose of this research is to implement the detector on mobile devices for mixed and augmented reality experiences, so a lighter weight SSD [1] model was designed while retaining its performance. The custom model is 4 times faster than the original SSD [1] model and the tests showed that it is even more accurate on the designated data set. The model is implemented in Python using Tensorflow and will soon be available on GitHub for public use.

This work aims to build a multimodal and open Augmented Reality application to enable overlaying videos or 3D graphics on natural objects in a real-time tracking process. The target object is detected within the sequence of images through its local points of interest and their corresponding descriptors. The similarity between the query and the reference image is computed and the homography relating 2D features is determined to produce the projective transformation used for the video registration mode. To add a 3D model into the scene, we estimate the real camera pose and we resolve the transformations connecting the virtual and the real camera reference frames. The obtained results from experiments are accurate and computationally effective. The developed system detects and tracks in real-time markerless objects, then overlays accurately videos or 3D graphics on targets.

Abstract In the last decade, there has been an extraordinary acceleration in immersive technologies, including virtual reality (VR) and augmented reality (AR). The VR interfaces have widely explored various 3D interaction‐based approaches. 3D interaction is one of the main features of any VR system. However, the problems while selecting and manipulating distant and occluded 3D virtual objects in VR are still unresolved and suffer from a lack of precision and accuracy. To interact with VR/AR systems, various devices such as VR headsets or gloves are used. These devices are not very reliable yet; in fact they are inconvenient and invasive to a person's comfort. Currently, the natural user interfaces (NUIs) are increasingly introduced in human computer interaction (HCI) systems as gestures recognition, which prove to be very useful in the improvement of the user engagement and presence sensing. More particularly, they provide more user‐friendly and nonintrusive 3D interaction methods and techniques. In this article, the Zoom‐fwd, which is an efficient 3D interaction technique is presented. The proposed technique uses gesture recognition for different 3D interaction tasks like selection and manipulation. This new approach allows an efficient interaction with distant and occluded objects, while providing a precise selection, even when the environment is crowded. The Zoom‐fwd technique is a software solution for a number of hardware and software problems. A user study is conducted to determine whether the proposed technique is more suitable when performing interaction tasks. The results show that the Zoom‐fwd technique provides effective interaction with distant and occluded objects, by improving the user task completion performance. In addition, this indicates that selection precision has been enhanced significantly with the Zoom‐fwd technique.

Mastering motor skills requires performing the task unconsciously with great speed and accuracy. This is acquired slowly through practice over time. Nonetheless, in domains such as surgery, the training of these skills in the field introduces safety, ethical and economic issues. In this context, immersive VR technologies offer the possibility to recreate real-world situations and allow the trainees to improve their skills in a safe and controlled environment. However, the design of such systems raises new research questions, such as how to represent the user in the virtual environment, and whether this representation can influence motor skills automaticity. In this work, we focus on how the user's hand representation can impact the training of tool-based motor skills in immersive VR. To investigate this question, we have created a VR simulator for training a tool-based pick and place task, and conducted a user study to evaluate how the user's hand visualization can influence participants' learning performance after a two-week training period. For that purpose, two groups of participants were trained in the VR simulator under one of the two experimental conditions: the presence and the absence of their virtual hands' representation, while a control group received no training. The results of the study show that training on the VR simulator improves the participants' motor task performance when compared with the control group. On the other hand, no difference was observed between the two training groups. This suggests that the user's hand visualization does not always impact tool-based motor tasks training in immersive VR simulators. Indeed, for short-term motor training there was no difference in performance between having a partial embodiment of the user's hands and only the tools representation.

Immersive VR technologies offer versatile training tools by recreating real-world situations in a virtual and safe environment and allowing users to have a first-person experience. The design of such training systems requires defining the most critical components to simulate, and to what extent they can be simulated successfully. One open research question for designing such systems is how to represent the user in the virtual environment, and which is the added value of this representation for training purposes. In this work, we focus on how the user's hand representation in an immersive virtual environment can impact the training of tool-based motor skills.To investigate this question, we have designed a VR trainer for a simple tool-based pick and place task. A user experiment was conducted to evaluate how the movements of the users' real hand representation influence their performance and subjective experience in the virtual environment. For that purpose, the participants performed the task on the VR simulator with two conditions: the presence or absence of their animated virtual hands representation. The results of this study show that, although users prefer to have a visual representation of their hands, they achieved similar and correlated performance in the VR system regardless of the hand representation condition. These results suggest that the presence of the user's hand representation is not necessary when performing a tool-based motor skill task in a VR trainer. These findings have practical implications for the design of VR simulators for training motor skills tasks since adding users' hand representation may require cumbersome and expensive additional devices.

International audience

In this paper, we present a low-cost virtual reality (VR) collaborative system equipped with a haptic feedback sensation system. This system is composed of a Kinect sensor for bodies and gestures detection, a microcontroller and vibrators to simulate outside interactions, and smartphone powered cardboard, all of this are put into a network implemented with Unity 3D game engine.

Virtual Reality simulators are increasingly used for training novice surgeons. However, there is currently a lack of guidelines for achieving interaction fidelity for these systems. In this paper, we present the design of two navigation techniques for a needle insertion trainer. The two techniques were analyzed using a state-of-the-art fidelity framework to determine their levels of interaction fidelity. A user study comparing both techniques suggests that the higher fidelity technique is more suited as a navigation technique for the needle insertion virtual trainer.

Interaction with computers using freehand gestures becomes more and more popular. However, it is hard to make precise inputs by making gestures in air without a physical support. In this paper, we present HorizontalDragger, a new selection technique aimed to improve the selection precision by converting the 2D selection problem into a 1D selection problem. After setting a region of interest in the display, all the objects inside the region are considered as potential targets. The user can drag the index finger horizontally to choose the desired target.

To make constrained manipulation of 3D objects in desktop 3D applications, 3D transformation widgets are commonly used. However, their performance degrades on touchscreens because of low accuracy of touch inputs and the fingertip occlusion problem. In this paper, we present TouchSketch, a touch-based interface which allows users to perform independently fine-grained object translation, rotation and scaling on mobile devices. Our manipulation technique permits using the non-dominant hand to specify the manipulation reference while the dominant hand is used to determine the operation mode and control the transformation. In addition to 3D manipulation, TouchSketch provides also a set of functions to edit the shape of 3D objects. Users can use this application to accomplish rapid sketching tasks. We have conducted a user study to evaluate the efficiency of our manipulation technique. The results show that our technique outperforms a Widget-based technique regarding both the efficiency and fluency.

This paper addresses the problem of stabilizing and trajectory tracking control of a remotely operated vehicle (ROV-Observer) in the vertical plane. The underwater vehicle is not actuated in the pitch direction and cannot be locally asymptotically stabilized by continuous feedbacks which are functions of the state only. In the present note, exponential convergence is obtained by considering time-varying feedbacks which are only continuous. Furthermore, using the backstepping technique and the tracking error dynamics, the system states are stabilized by forcing the tracking errors to an arbitrarily small neighborhood of zero.

This paper presents a method to design an observer-based controller that simultaneously solves global estimation of state and asymptotic stabilization of an underactuated remotely operated vehicle moving in the in three-dimensional. The vehicle does not have a sway and roll actuator and has only position and orientation measurements available. The control development is based on Lyapunov's direct method for nonlinear system.

In this paper, we propose an efficient, and fast binary descriptor, called MOBIL (MOments based BInary differences for Local description), which compares not just the intensity, but also sub-regions geometric proprieties by employing moments. This approach offers high distinctiveness against affine transformations and appearance changes. The experimental evaluation shows that MOBIL achieves a quite good performance in term of low computation complexity and high recognition rate compared to state-of-the-art real-time local descriptors.

In this paper, we present three freehand interaction techniques for 3D content manipulation, the FingerShake, for object translation, the FingerRotate, for object rotation and the FingerSwing for object scale. These three techniques refer to a more generic concept which we call FingerOscillation. The main contribution is to interact with the machine by using finger oscillation movements. We introduce the design and the implementation of these techniques.

This work focuses on enabling 3D interaction assistance by adding adaptivity depending on the tasks, objectives, and the general interaction context. We model the context using Conceptual Graphs (CG) based on an ontology. Including CG in our scene manager (Virtools) allows us to add semantic information and to describe the available tools. We handle rules leading to adaptation with a logic programming layer (Prolog+CG) included in the Amine platform. This project is a step towards Intelligent Virtual Environments, which proposes a hybrid solution by adding a separate semantic reasoning to classic environments. The first case study automatically manages few modalities depending on the distance to objects, user movement, available tools and modality risks.

The introduction of virtual and mixed realities in aquatic leisure activities constitutes a technological rupture when compared with the status of related technologies. With the extension of Internet to underwater applications, the innovative character of the project becomes evident, and the impact of this development in the littoral and beach tourism may be considerable. In fact, there are recent developments to extend the use of computers and computer components, such as the mouse, to underwater uses. The Dolphyn is an underwater-computerized display system with various sensors and devices conceived for existing swimming pools and for beach shores, associating computer functions, video gaming and multisensory simulations.

We propose a semantic reasoning engine for context-awareness in classic VR environments. It is currently used to automatically detect user's interests and manage visual enhancements depending on the user's movement.

In this paper, we propose a machine-machine collaboration formalism to support groupware tailorability. Our work is based on the 3C functional model by Ellis that decomposes collaboration between users into communication, coordination and cooperation phases. Through our research, we realized that Web services are powerful distributed components offering the desired tools in order to adapt a groupware system to the real needs of users. Therefore, we use this technology to define a collaboration protocol between machines over the network for implementing tailorability in CSCW systems. A groupware architecture is presented based on the proposed formalism. We argue that a protocol between machines over the internet should be defined in order to exchange common services in real time collaboration.

In this paper, we propose a software architecture based on Web services and Software agents for groupware tailorability. Through our literature study, we realize that the property of tailorability has a significant impact on designing collaborative applications. Although online applications in the recent years have been growing exponentially, online collaborative work between users is often supported by software applications that provide static basic functionalities, mostly centered on communication tools (text, audio and video). Hence, adding more sophisticated tools for enriching the collaborative experience, as for example, an integrated environment for task coordination and production, requires manually coding them into the application, which requires a significant effort in order to adapt the system to the real needs of users. In a collaborative context, the application designers are not able to predict all users' needs at design time. To remedy this problem, we propose a tailorable groupware architecture that enables the dynamic integration/composition of services into the collaborative application, gaining both in time and performance. Our work is based on the 3C functional model by Ellis that decomposes collaboration between users into communication, coordination and cooperation spaces. Through our research, we realized that Web services are powerful distributed components offering the desired tools to adapt a groupware to the real needs of users. In this paper, we propose a collaboration protocol based on Web services between machines over the network in order to exchange common services. Based on this protocol, we propose our groupware architecture, U3D, that introduces tailorability in collaboration applications.

Behind its spatial organization, the DNA's molecule conceals a rich functional reality. As a result, the study of the DNA's organization is increasingly attracting scientists. However, researches conducted until now are either local, or global but based on approximations and predictions that make the obtained model less credible. On the other hand, further researches on chromosomes' organization have identified some data and models representing, each one, a part of this organization. Our work aims to find a 3D repesentation that is global and more credible of the DNA's molecule. The molecule will be represented at the chromatin fiber level by means of 3D modeling algorithms. Initially, we have identified the biophysical data to be exploited. Indeed, we will first rely on the biophysical data of the chromatin fiber's structure as the persistence length along with the diameter, the confined volume and the curvature energy in order to build a first simple model of the chromatine.

VR systems need more and more sensors to provide the most efficient 3D interaction in the virtual world. With the multiplication of sensors in these systems, new constraints emerged, especially how to process the huge amount of incoming data and how to estimate a correct interpretation from it. However data processing is often a complex approach. In this paper, we present to you a framework that can be used such an upper-layer on the hardware layer to provide data processing and data fusion to a virtual reality application.

In this paper, we present a research work in the context of a national project, DIGITAL OCEAN for the creation and distribution of multimedia content, where we present tailorable groupware architecture, Oce@nyd, to allow a collaborative collection of multimedia information over the Internet. The Oce@nyd architecture is based on Web services and software agents' integration. This research is, until now, never been exploited in the context of groupware tailorability, hence bringing innovation in the CSCW (Computer Supported Cooperative Work) domain. We apply our research work on DIGITAL OCEAN in order to give users means to collaborate more efficiently, for the purpose of enriching underwater maps with up-to-date multimedia files, as well as means to tailor the services proposed in the system in order to adapt the system to their preferences, and hence enhance collaboration.

Augmented Reality (AR) can provide to a Human Operator (HO) a real help to achieve complex tasks, such as remote control of robots and cooperative teleassistance. Using appropriate augmentations, the HO can interact faster, safer and easier with the remote real world. In this paper, we present an extension of an existing distributed software and network architecture for collaborative teleoperation based on networked human-scaled mixed reality and mobile platform. The first teleoperation system was composed by a VR application and a Web application. However the 2 systems cannot be used together and it is impossible to control a distant robot simultaneously. Our goal is to update the teleoperation system to permit a heterogeneous collaborative teleoperation between the 2 platforms. An important feature of this interface is based on the use of different Virtual Reality platforms and different Mobile platforms to control one or many robots. The first aim with this work is to develop collaborative robot teaching with the use of virtual or real robot.

In this article, we propose an approach to introduce tailorability in the design of groupware, as the approaches already existing are still ambiguous in putting it forward in CSCW systems. We will present a brief overview on some approaches that deals with tailorability in this field. Then, we will make use of concepts and notions from each in order to integrate them in an innovative, value-added and tailorable architecture. We will discuss the purpose of integrating Internet technologies with software agents while putting it forward in the context of tailorable groupware design.

Human Operators (HO) of telerobotics systems may be able to achieve complex operations with robots. Designing usable and effective Human-Robot Interaction (HRI) is very challenging for system developers and human factors specialists. The search for new metaphors and techniques for HRI adapted to telerobotics systems emerge on the conception of Multimodal HRI (MHRI). MHRI allows to interact naturally and easily with robots due to combination of many devices and an efficient Multimodal Management System (MMS). A system like this should bring a new user's experience in terms of natural interaction, usability, efficiency and flexibility to HRI system. So, a good management of multimodality is very. Moreover, the MMS must be transparent to user in order to be efficient and natural.

In this paper, we present a new groupware architectural model called UD3, which is based on the integration of web services technologies with software agents. The aim is to design a tailorable groupware architecture using the integration of both technologies, thus using properties of each while reinforcing their individual strengths. In fact, agent-oriented technology is claimed to become the next breakthrough in the development and implementation of large-scale complex systems, while Web services are fast emerging technologies for connecting remotely executing programs via well established internet protocols. Web services and agents were originally developed with different standards, thus their integration becomes important in the context of groupware tailorability, giving a totally innovative approach for designing collaborative applications.

Design of complex systems requires multi-user cooperation with virtual reality technologies to provide 3D interactions between users and virtual objects. Recent advances in both virtual reality (VR) systems and computer-supported cooperative work (CSCW) technologies have resulted in a convergence of the appearance of the collaborative virtual environments (CVEs) systems supporting different forms of collaboration and interaction between users. The collaboration in these systems refers to the simultaneous interactions (collaborative interaction) of multiple users on a virtual object in an immersive or semi-immersive virtual environment. In this paper, we propose a method to modeling collaborative 3D interactions that supports group interaction in CVEs. The proposed method is based on group awareness concepts (focus and nimbus) combined astutely with 3D interaction paradigms (navigation, selection and manipulation) to provide us a collaborative 3D interaction model needed to design an adaptive workflow for coordination of multi-user 3D interactions in CVEs.

This paper gives preliminary results about the utilization of an interaction technique called FOLLOW-ME to fasten the selection task for teleoperation system. The implementation of an interaction between a user and a virtual environment (VE) in virtual reality (VR) may use various techniques. However, in the case of teleoperation, the interaction must be very precise and comfortable for the user. The model associated to the FOLLOW-ME technique splits the virtual environment into three zones in which a specific interaction model is used: a free manipulation zone, a scaled manipulation zone and a precise manipulation zone. Each one of the three zones is characterized by a specific interaction granularity. In the precise manipulation zone, we use the concept of virtual guides in order to assist the user to achieve his task. In this paper, our aim is to show that the FOLLOW-ME technique is well suited for selection in teleoperation tasks. To do this, we have first compared the FOLLOW-ME technique with classical interaction techniques in a virtual environment where different targets are situated at different depth and may move. The preliminary results show that our technique is more efficient than the classical go-go and ray-casting techniques, in a sense that the task is more reproducible and easier to accomplish by the user. In a second stage, we use this result to design selection procedures for the ARITI tele-operation system and show that the use of FOLLOW-ME induces benefits for the user