is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This article proposes a method based on wavelet transform and neural networks for relating pupillary behavior to psychological stress. The proposed method was tested by recording pupil diameter and electrodermal activity during a simulated driving task. Self-report measures were also collected. Participants performed a baseline run with the driving task only, followed by three stress runs where they were required to perform the driving task along with sound alerts, the presence of two human evaluators, and both. Self-reports and pupil diameter successfully indexed stress manipulation, and significant correlations were found between these measures. However, electrodermal activity did not vary accordingly. After training, the four-way parallel neural network classifier could guess whether a given unknown pupil diameter signal came from one of the four experimental trials with 79.2% precision. The present study shows that pupil diameter signal has good discriminating power for stress detection.

International audienceNavigation in a 3D immersive virtual environment is known to be prone to visually induced motion sickness (VIMS). Several psychophysiological and behavioral methods have been used to measure the level of sickness of a user, among which is postural instability. This study investigates all the features that can be extracted from the body postural sway: area of the projection of the center of gravity (mainly considered in past studies) and its shape and the frequency components of the signal's spectrum, in order to estimate and predict the occurrence of sickness in a typical virtual reality (VR) application. After modeling and simulation of the body postural sway, an experiment on 17 subjects identified a relation between the level of sickness and the variation both in the time and frequency domains of the body sway signal. The results support and go further into detail of findings of past studies using postural instability as an efficient indicator of sickness, giving insight to better monitor VIMS in a VR application

This paper describes a motion generation method for dynamic lifting by a humanoid robot. The proposed technique suggests the possibility of taking advantage of the whole body motion in order to facilitate the lifting movement. In particular, the idea is to perform a preliminary motion in order to generate a momentum which is instantaneously transferred to the object as an impulsive force. This allows the humanoid to lift up an object that could not be lifted up only by continuous force. However an impulsive force may make the humanoid unstable. Then, we propose to set the center of percussion (CoPn) of the whole system at the center of the support polygon of the humanoid when it lifts up the object. We also propose a design method of a preliminary motion of the humanoid that generates a sufficient momentum to lift up an object without any slip, tumble and hop of the whole system. The effectiveness of the proposed method is confirmed by simulation and experiment.

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There are many kinds of large, heavy objects, or objects with geometrical constraints in our daily life, but non-fixed robots such as humanoid robots are still not able to manipulate them sufficiently well. In this paper we focus on a swing door as a heavy object with geometrical constraints, and present a method for the humanoid robots to open it by using impulsive forces. We first discuss on momentum transfer from the robot to the door. Then we propose a method of generating a whole body motion to impact on the door. We analyze the dynamic model of the door, and we confirm the validity of our method through simulation. At last, we realize a motion of the robot opening a swing door quickly by the method in experiment with the HRP-2 robot hardware.

Abstract-A motion control method of lifting a heavy object up to a higher position with humanoid robots is developed. The key issue of lifting motion is how to reduce the load on humanoid arms in which low-power actuators are implemented. The use of singular postures of arms is well-known to avoid actuator saturation of the arms. By combining two different kinds of humanoid motions such as accelerating an object upward and sliding the body into under the object, we propose a method that enables to transit one singular posture of arms to another while lifting the object. Simulation results show the effectiveness of the proposed method for reducing the load on the arms. We realize a motion of lifting a heavy object dynamically with the humanoid robot HRP-2 through experiment.

With an ability to mimic the human behaviour, humanoid robots have become a topic of major interest among research fellows dealing with robotic investigation. The current work is focussed on the design of a novel navigational controller based on the logic of the regression analysis to be used in the path planning and navigation of humanoid robots. In the current investigation, static and dynamic path planning of humanoid NAOs are encountered. The static path planning represents a single NAO navigating through random static obstacles. The dynamic path planning represents multiple humanoid NAOs navigating through random static obstacles and acting as dynamic obstacles for each other. A Petri-Net controller is designed to avoid the collision among the multiple NAOs in dynamic path planning. To reduce the path length and time travel and to provide the shortest possible path, an advanced regression controller is implemented in the NAOs in both simulation and experimental environments. Finally, a comparison has been performed between the simulation and experimental results, and a good agreement is observed between both the results with a minimal percentage of error. The proposed navigational controller is also tested against other existing navigational technologies to validate better efficiency.

During 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.