To avoid crashing onto the floor, a free falling fly needs to trigger its wingbeats quickly and control the orientation of its thrust accurately and swiftly to stabilize its pitch and hence its speed. Behavioural data have suggested that the vertical optic flow produced by the fall and crossing the visual field plays a key role in this anti-crash response. Free fall behavior analyses have also suggested that flying insect may not rely on graviception to stabilize their flight. Based on these two assumptions, we have developed a model which accounts for hoverflies´ position and pitch orientation recorded in 3D with a fast stereo camera during experimental free falls. Our dynamic model shows that optic flow-based control combined with closed-loop control of the pitch suffice to stabilize the flight properly. In addition, our model sheds a new light on the visual-based feedback control of fly´s pitch, lift and thrust. Since graviceptive cues are possibly not used by flying insects, the use of a vertical reference to control the pitch is discussed, based on the results obtained on a complete dynamic model of a virtual fly falling in a textured corridor. This model would provide a useful tool for understanding more clearly how insects may or not estimate their absolute attitude.

Virtual reality (driving simulators) tends to generalize for the study of human behavior in mobility. It is thus crucial to ensure that perception of space and motion is little or not affected by the virtual environment (VE). The aim of this study was to determine a metrics of distance perception in VEs and whether this metrics depends on interactive factors: stereoscopy and motion parallax. After a training session, participants were asked, while driving, to estimate the relative location (5 to 80 m) of a car on the same road. The overall results suggest that distance perception in this range does not depend on interactive factors. In average, as generally reported, subjects underestimated the distances whatever the vision conditions. However, the study revealed a large interpersonal variability: two profiles of participants were defined, those who quite accurately perceived distances in VR and those who underestimated distances as usually reported. Overall, this classification was correlated to the level of performance of participants during the training phase. Furthermore, learning performance is predictive of the behavior of participants.

Despite growing interest over the decades, the question of estimating cognitive workload of operators involved in complex multitask operations, such as helicopter pilots, remains a key issue. One of the main difficulties facing workload inference models is that no single specific indicator of workload exists, so that multiple sources of information have to be inputted to the model. The question then arises as to the nature and the quantity of features to be used for increasing model performance. In this research, done in cooperation with Eurocopter, the effectiveness of physiological, psychological, and cognitive features for estimating helicopter pilots' workload was systematically investigated, using Bayesian networks (BNs). The study took place in two different contexts: a constrained laboratory situation with low ecological validity and a more realistic and challenging situation relying on virtual reality. The constrained conditions of the laboratory study allowed us for testing various combinations of entropy-based physiological, cognitive, and affect features as inputs of BN models. These three different kinds of features are shown to carry complementary information that can be used with advantage by the model. The results also suggest that increasing the number of physiological inputs improves the model performance. The second study aimed at challenging some of these conclusions in a more ecological context, by using the NH90 full-flight simulator of the Helisim company. The results emphasize the problem of accessing the ground truth, as well as the need for an efficient feature selection or extraction step prior to the classification step.

This paper presents an approach based on Bayesian Networks to estimate the workload of operators. The models take as inputs the entropy of different number of physiological features, as well as a cognitive feature (reaction time to a secondary task). They output the workload variation of subjects involved in successive tasks demanding different levels of cognitive resources. The performances of the classifiers are discussed in term of two criteria to be jointly optimized: the diversity, i.e. the ability of the model to perform on different subjects, and the accuracy, i.e., how close from the (subjectively estimated) workload level the model prediction is.

Shape and mechanical structure of instruments play a large part in the lack of ergonomics during laparoscopic surgery. Providing intra-abdominal mobility and rethinking handles design are two solutions to increase comfort and precision of gestures. Based on previous work that determined the optimal intra-abdominal kinematics, this study analyses the influence of handle design on both gesture and ergonomic performance. A virtual reality laparoscopic simulator was developed to perform an experimental comparison between two novel robotized instruments and standard ones. A group of 10 surgeons and 6 researchers in robotics carried out two representative surgical tasks with each instrument. Based on instrument and arm segments tracking, a gesture performance index and an ergonomic performance index were computed. The study demonstrates that distal mobilities combined with improved handle design and integration increase ergonomic level during laparoscopy and facilitate complex gestures.

While modern dynamic driving simulators equipped with six degrees-of-freedom (6-DOF) hexapods and X-Y platforms have improved realism, mechanical limitations prevent them from offering a fully realistic driving experience. Solutions are often sought in the ”washout” algorithm, with linear accelerations simulated by an empirically chosen combination of translation and tilt-coordination, based on the incapacity of otolith organs to distinguish between inclination of the head and linear acceleration. In this study, we investigated the most effective combination of tilt and translation to provide a realistic perception of movement. We tested 3 different braking intensities (deceleration), each with 5 inverse proportional tilt/translation ratios. Subjects evaluated braking intensity using an indirect method corresponding to a 2-Alternative-Forced-Choice Paradigm. We find that perceived intensity of braking depends on the tilt/translation ratio used: for small and average decelerations (0.6 and 1.0m/s2), increased tilt yielded an increased overestimation of braking, inverse proportionally with intensity; for high decelerations (1.4m/s2), on half the conditions braking was overestimated with more tilt than translation and underestimated with more translation than tilt. We define a mathematical function describing the relationship between tilt, translation and the desired level of deceleration, intended as a supplement to motion cueing algorithms, that should improve the realism of driving simulations.

The authors evaluate the performance and try to identify the strategies of human operators (HOs) teleoperating a robot along 2-D-trajectories in simulations of place-like tasks in an obstacle encumbered environment. The experiments utilize computer graphic simulations of a remote robot whose end-effector displacements are dynamically controlled in the X-Y plane by the HO's hand displacements. The performance is described in the various displayed conditions in terms of movement duration, spatial and temporal errors, and energy. The data show that performance depends on the nature of the cues and instructions provided to the operators. Comparative analysis of the various conditions suggests that visual feedback position control is used when continuous static or dynamic information about the trajectory is provided, while feedforward control, corrected by sampled visual information, is adopted when a self-generated movement can be planned and executed. The data also show that for a given set of execution cues, equivalent performance is achieved in both visual frames of reference.>

Some problems raised by bimanual coordination control of articulated systems are studied. In particular, the performance of human operators driving an anthropomorphic robot along 3-D trajectories using either a bimanual micromanipulator or a keypad is compared. The trajectories were materialized in space by a thin wire twisted to trace a cosine wave. The performance was quantified in terms of total time (that is, the time to drive the robot effector through the trajectory), cumulated error, standard deviation and maximum error along the trajectory.>