127 research outputs found
Monitoring a Realistic Virtual Hand using a Passive Haptic Device to Interact with Virtual Worlds
We present a prototype of a hands-on immersive peripheral device for controlling a virtual hand with high dexterity. This prototype is as easy as a mouse to use and allows the control of a high number of degrees of freedom (dofs) with tactile feedback. The goals corresponding to design issues, physiological behaviors, include the choice of sensors’ technology and their position on the device, low forces exerted while using the device, relevant multi-sensorial feedback, performance of achieved tasks
Périphérique d'interaction apte à contrôler un élément de toucher et de préhension d'objets virtuels multidimensionnels
Ne pas le transférer sur HAL (déjà déposé sur HAL par le co-auteur (hors ENSAM))L’invention concerne un périphérique d’interaction (1) apte à contrôler un élément de toucher et de préhension d’objets virtuels multidimensionnels, comportant au moins deux modules d’interaction (20), chaque module d’interaction (20) étant destiné à être actionné par un doigt d’un opérateur et comportant un capteur de commande permettant de commander un déplacement, selon un nombre de degrés de liberté prédéterminé, d’une partie de l’élément de toucher et de préhension d’objets virtuels par déplacement en flexion/extension et/ou adduction/abduction du doigt de l’opérateur, et un vibreur apte à émettre une vibration lors du toucher et/ou du lâcher d’un objet virtuel par une partie dudit élément de toucher et de préhension d’objets virtuels, caractérisé en ce que chaque module d’interaction (20) est fixé audit périphérique par une jonction (40) en matériau amortissant
Virtual Distance Estimation in a CAVE
Past studies have shown consistent underestimation of distances in virtual reality, though the exact causes remain unclear. Many virtual distance cues have been investigated, but past work has failed to account for the possible addition of cues from the physical environment. We describe two studies that assess users' performance and strategies when judging horizontal and vertical distances in a CAVE. Results indicate that users attempt to leverage cues from the physical environment when available and, if allowed, use a locomotion interface to move the virtual viewpoint to facilitate this
Design of a Semiautomatic Travel Technique in VR Environments
International audienceTravel in a real environment is a common task that human beings conduct easily and subconsciously. However transposing this task in virtual environments (VEs) remains challenging due to input devices and techniques. Considering the well-described sensory conflict theory, we present a semiautomatic travel method based on path planning algorithms and gaze-directed control, aiming at reducing the generation of conflicted signals that may confuse the central nervous system. Since gaze-directed control is user-centered and path planning is goal-oriented, our semiautomatic technique makes up for the deficiencies of each with smoother and less jerky trajectories
VR Sickness Prediction for Navigation in Immersive Virtual Environments using a Deep Long Short Term Memory Model
International audienceThis paper proposes a new objective metric of visually induced motion sickness (VIMS) in the context of navigation in virtual environments (VEs). Similar to motion sickness in physical environments, VIMS can induce many physiological symptoms such as general discomfort, nausea, disorientation, vomiting, dizziness and fatigue. To improve user satisfaction with VR applications, it is of great significance to develop objective metrics for VIMS that can analyze and estimate the level of VR sickness when a user is exposed to VEs. One of the well-known objective metrics is the postural instability. In this paper, we trained a LSTM model for each participant using a normal-state postural signal captured before the exposure, and if the postural sway signal from post-exposure was sufficiently different from the pre-exposure signal, the model would fail at encoding and decoding the signal properly; the jump in the reconstruction error was called loss and was proposed as the proposed objective measure of simulator sickness. The effectiveness of the proposed metric was analyzed and compared with subjective assessment methods based on the simulator sickness questionnaire (SSQ) in a VR environment, achieving a Pearson correlation coefficient of .89. Finally, we showed that the proposed method had the potential to be deployed within a closed-loop system and get real-time performance to predict VR sickness, opening new insights to develop user-centered and customized VR applications based on physiological feedback
Modeling online adaptive navigation in virtual environments based on PID control
It is well known that locomotion-dominated navigation tasks may highly
provoke cybersickness effects. Past research has proposed numerous approaches
to tackle this issue based on offline considerations. In this work, a novel
approach to mitigate cybersickness is presented based on online adaptative
navigation. Considering the Proportional-Integral-Derivative (PID) control
method, we proposed a mathematical model for online adaptive navigation
parameterized with several parameters, taking as input the users'
electro-dermal activity (EDA), an efficient indicator to measure the
cybersickness level, and providing as output adapted navigation accelerations.
Therefore, minimizing the cybersickness level is regarded as an argument
optimization problem: find the PID model parameters which can reduce the
severity of cybersickness. User studies were organized to collect non-adapted
navigation accelerations and the corresponding EDA signals. A deep neural
network was then formulated to learn the correlation between EDA and navigation
accelerations. The hyperparameters of the network were obtained through the
Optuna open-source framework. To validate the performance of the optimized
online adaptive navigation developed through the PID control, we performed an
analysis in a simulated user study based on the pre-trained deep neural
network. Results indicate a significant reduction of cybersickness in terms of
EDA signal analysis and motion sickness dose value. This is a pioneering work
which presented a systematic strategy for adaptive navigation settings from a
theoretical point
Visually Induced Motion Sickness Estimation and Prediction in Virtual Reality using Frequency Components Analysis of Postural Sway Signal
The paper proposes a method for estimating and predicting visually induced motion sickness (VIMS) occurring in a navigation task in a 3D immersive virtual environment, by extracting features from the body postural sway signals in both the time and frequency domains. Past research showed that the change in the body postural sway may be an element for characterizing VIMS. Therefore, we conducted experiments in a 3D virtual environment where the task was simply a translational movement with different navigation speeds. By measuring the evolution of the body's center of gravity (COG), the analysis of the sway signals in the time domain showed a dilation of the COG's area, as well as a change in the shape of the area. Frequency Components Analysis (FCA) of the sway signal gave an efficient feature to estimate and predict the level of VIMS. The results provide promising insight to better monitor sickness in a virtual reality application.FUI Callist
Virtual Distance Estimation in a CAVE
Past studies have shown consistent underestimation of distances in virtual reality, though the exact causes remain unclear. Many virtual distance cues have been investigated, but past work has failed to account for the possible addition of cues from the physical environment. We describe two studies that assess users’ performance and strategies when judging horizontal and vertical distances in a CAVE. Results indicate that users attempt to leverage cues from the physical environment when available and, if allowed, use a locomotion interface to move the virtual viewpoint to facilitate this.FUI in the framework of the Callisto projec
Dexterous Grasping Tasks Generated With an Add-on End Effector of a Haptic Feedback System
The simulation of grasping operations in virtual reality (VR) is required for many applications, especially in the domain of industrial product design, but it is very difficult to achieve without any haptic feedback. Force feedback on the fingers can be provided by a hand exoskeleton, but such a device is very complex, invasive, and costly. In this paper, we present a new device, called HaptiHand, which provides position and force input as well as haptic output for four fingers in a noninvasive way, and is mounted on a standard force-feedback arm. The device incorporates four independent modules, one for each finger, inside an ergonomic shape, allowing the user to generate a wide range of virtual hand configurations to grasp naturally an object. It is also possible to reconfigure the virtual finger positions when holding an object. The paper explains how the device is used to control a virtual hand in order to perform dexterous grasping operations. The structure of the HaptiHand is described through the major technical solutions required and tests of key functions serve as validation process for some key requirements. Also, an effective grasping task illustrates some capabilities of the HaptiHand
Design of an immersive peripheral for object grasping
Technical Committee Best Paper AwardInternational audienceDuring product development processes, simulations involving user's grasping operations are of increasing interest to incorporate more quantitative information in DFA (Design For Assembly) or immersive simulations. We present several prototypes of an immersive peripheral device for controlling a virtual hand with fine dexterity. These prototypes are derived from the analysis of a grasping action to define the structure and main features of this device. The prototypes, as easy to manipulate as a computer mouse, enable the simultaneous control of a large number of degrees of freedom (dofs). The design issues, where physical phenomena, physiological behavior and device structure are all tightly combined and significantly influence the overall interaction, are reviewed. These issues include the generation of dofs, monitoring kinematics, force reduction during virtual hand and finger movements, and the influence of device design, sensor types and their placement on the interaction and on the range of configurations that can be achieved for grasping tasks, dexterity, and performance. Examples of grasping tasks show the effect of these immersive devices to reach user-friendly and efficient interactions with objects bringing new insight to the interaction with virtual products
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