In this study, an analysis of brain, cardiovascular and respiratory dynamics was conducted combining information-theoretic measures with the Network Physiology paradigm during different levels of mental stress. Starting from low invasive recordings of electroencephalographic, electrocardiographic, respiratory, and blood volume pulse signals, the dynamical activity of seven physiological systems was probed with one-second time resolution measuring the time series of the $\delta$ , $\theta$ , $\alpha$ and $\beta$ brain wave amplitudes, the cardiac period (RR interval), the respiratory amplitude, and the duration of blood pressure wave propagation (pulse arrival time, PAT). Synchronous 5-min windows of these time series, obtained from 18 subjects during resting wakefulness (REST), mental stress induced by mental arithmetic (MA) and sustained attention induced by serious game (SG), were taken to describe the dynamics of the nodes composing the observed physiological network. Network activity and connectivity were then assessed in the framework of information dynamics computing the new information generated by each node, the information dynamically stored in it, and the information transferred to it from the other network nodes. Moreover, the network topology was investigated using directed measures of conditional information transfer and assessing their statistical significance. We found that all network nodes dynamically produce and store significant amounts of information, with the new information being prevalent in the brain systems and the information storage being prevalent in the peripheral systems. The transition from REST to MA was associated with an increase of the new information produced by the respiratory signal time series (RESP), and that from MA to SG with a decrease of the new information produced by PAT. Each network node received a significant amount of information from the other nodes, with the highest amount transferred to RR and the lowest transferred to $\delta$ , $\theta$ , $\alpha$ and $\beta$ . The topology of the physiological network underlying such information transfer was node- and state-dependent, with the peripheral subnetwork showing interactions from RR to PAT and between RESP and RR, PAT consistently across states, the brain subnetwork resulting more connected during MA, and the subnetwork of brain–peripheral interactions involving different brain rhythms in the three states and resulting primarily activated during MA. These results have both physiological relevance as regards the interpretation of central and autonomic effects on cardiovascular and respiratory variability, and practical relevance as regards the identification of features useful for the automatic distinction of different mental states.

The ability to produce 3D maps with infrared radiometric information is of great interest for many applications, such as rover navigation, industrial plant monitoring, and rescue robotics. In this paper, we present a system for large-scale thermal mapping based on IR thermal images and 3D LiDAR point cloud data fusion. The alignment between the point clouds and the thermal images is carried out using the extrinsic camera-to-LiDAR parameters, obtained by means of a dedicated calibration process. Rover’s trajectory, which is necessary for point cloud registration, is obtained by means of a LiDAR Simultaneous Localization and Mapping (SLAM) algorithm. Finally, the registered and merged thermal point clouds are represented through an OcTree data structure, where each voxel is associated with the average temperature of the 3D points contained within. Furthermore, the paper presents in detail the method for determining extrinsic parameters, which is based on the identification of a hot cardboard box. Both methods were validated in a laboratory environment and outdoors. It is shown that the developed system is capable of locating a thermal object with an accuracy of up to 9 cm in a 45 m map size with a voxelization of 14 cm.

This work presents an analysis and validation of a foldable boom actuated by tape-spring foldable elastic hinges for space applications. The analytical equations of tape-springs are described, extending the classical equations for isotropic materials to orthotropic carbon-fiber composite materials. The analytical equations which describe the buckling of the hinge have been implemented in a multibody simulation software where the hinge was modeled as a nonlinear elastic bushing and the boom as a rigid body. In the experimental phase, the boom was fabricated using a thin layer carbon-fiber composite tube, and the residual vibrations after deployment were experimentally tested with a triaxial accelerometer. A direct comparison of the simulation with the physical prototype pointed out the dangerous effect of higher order vibrations which are difficult to capture in simulation. We observed that while the vibrational spectra of simulations and experiments were compatible at low frequencies during deployment, a marked difference was observed at frequencies beyond 30 Hz. While difficult to model, higher order frequencies should be carefully accounted for in the design of self-deployable space structures. Indeed, if tape-springs are used as a self-locking mechanism, the higher vibrational modes could have enough energy to unlock the structure during operation.

Monocular vision systems allow compact and resource-constrained vehicles to perform online state estimation through Structure from Motion approaches. However, it is needed to integrate additional information to obtain a metric scale for the estimated trajectory. We propose a minimalistic approach based on the sensor fusion between a monocular camera and a 1D LiDAR (LIght Detection And Ranging) rangefinder. A classical visual front-end, in charge of tracking the camera pose with respect to a map of landmarks, is paired with an optimization back-end where depth measurements constrain the distance between cameras and 3D points. The fusion methodology is based on a keyframe-wise search of correspondences between visual landmarks and projections of altimeter points. The differences between triangulated landmark depths and associated altimeter measurements are minimized using the iSAM2 incremental smoother. We test our algorithm in a variety of datasets comprising an outdoor scenario with accurate D-GPS ground truth evaluating both tracking accuracy and computational effort. Results show that our algorithm provides comparable performances to scale-aware RGB-D vision systems and obtains relative trajectory errors close to 0.5%. Furthermore, we propose and validate an extrinsic calibration pipeline to refer range measurements in the camera reference system which differs from common LiDAR-camera calibration algorithms due to the 5 Degrees of Freedom (DoF) nature of the single-point rangefinder and camera system.

Any severe motor disability is a condition that limits the ability to interact with the environment, even the domestic one, caused by the loss of control over one’s mobility. This work presents RoboEYE, a power wheelchair designed to allow users to move easily and autonomously within their homes. To achieve this goal, an innovative, cost-effective and user-friendly control system was designed, in which a non-invasive eye tracker, a monitor, and a 3D camera represent some of the core elements. RoboEYE integrates functionalities from the mobile robotics field into a standard power wheelchair, with the main advantage of providing the user with two driving options and comfortable navigation. The most intuitive and direct modality foresees the continuous control of frontal and angular wheelchair velocities by gazing at different areas of the monitor. The second, semi-autonomous modality allows navigation toward a selected point in the environment by just pointing and activating the wished destination while the system autonomously plans and follows the trajectory that brings the wheelchair to that point. The purpose of this work was to develop the control structure and driving interface designs of the aforementioned driving modalities taking into account also uncertainties in gaze detection and other sources of uncertainty related to the components to ensure user safety. Furthermore, the driving modalities, in particular the semi-autonomous one, were modeled and qualified through numerical simulations and experimental verification by testing volunteers, who are regular users of standard electric wheelchairs, to verify the efficiency, reliability and safety of the proposed system for domestic use. RoboEYE resulted suitable for environments with narrow passages wider than 1 m, which is comparable with a standard domestic door and due to its properties with large commercialization potential.