Qualitative design and implementation of human-robot spatial interactions

Despite the large number of navigation algorithms available for mobile robots, in many social contexts they often exhibit inopportune motion behaviours in proximity of people, often with very "unnatural" movements due to the execution of segmented trajectories or the sudden activation of safety mechanisms (e.g., for obstacle avoidance). We argue that the reason of the problem is not only the difficulty of modelling human behaviours and generating opportune robot control policies, but also the way human-robot spatial interactions are represented and implemented. In this paper we propose a new methodology based on a qualitative representation of spatial interactions, which is both flexible and compact, adopting the well-defined and coherent formalization of Qualitative Trajectory Calculus (QTC). We show the potential of a QTC-based approach to abstract and design complex robot behaviours, where the desired robot's behaviour is represented together with its actual performance in one coherent approach, focusing on spatial interactions rather than pure navigation problems

A bank of unscented Kalman filters for multimodal human perception with mobile service robots

A new generation of mobile service robots could be ready soon to operate in human environments if they can robustly estimate position and identity of surrounding people. Researchers in this field face a number of challenging problems, among which sensor uncertainties and real-time constraints. In this paper, we propose a novel and efficient solution for simultaneous tracking and recognition of people within the observation range of a mobile robot. Multisensor techniques for legs and face detection are fused in a robust probabilistic framework to height, clothes and face recognition algorithms. The system is based on an efficient bank of Unscented Kalman Filters that keeps a multi-hypothesis estimate of the person being tracked, including the case where the latter is unknown to the robot. Several experiments with real mobile robots are presented to validate the proposed approach. They show that our solutions can improve the robot's perception and recognition of humans, providing a useful contribution for the future application of service robotics

Computationally efficient solutions for tracking people with a mobile robot: an experimental evaluation of Bayesian filters

Modern service robots will soon become an essential part of modern society. As they have to move and act in human environments, it is essential for them to be provided with a fast and reliable tracking system that localizes people in the neighbourhood. It is therefore important to select the most appropriate filter to estimate the position of these persons. This paper presents three efficient implementations of multisensor-human tracking based on different Bayesian estimators: Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Sampling Importance Resampling (SIR) particle filter. The system implemented on a mobile robot is explained, introducing the methods used to detect and estimate the position of multiple people. Then, the solutions based on the three filters are discussed in detail. Several real experiments are conducted to evaluate their performance, which is compared in terms of accuracy, robustness and execution time of the estimation. The results show that a solution based on the UKF can perform as good as particle filters and can be often a better choice when computational efficiency is a key issue

High occurrence of Flavescence dorée phytoplasma early in the season on grapevines infected with grapevine yellows

Research NoteA survey for the presence of phytoplasmas associated with grapevine yellows in about 500 Italian vineyards was conducted from 1999 to 2004. Grapevines with the earliest symptoms were mostly infected with Flavescence dorée type C phytoplasma (FD-C). As the season advanced, a steady relative decrease in the occurrence of FD-C coincided with a clear relative increase in Bois noir phytoplasma. The relative occurrence of Flavescence dorée type D phytoplasma remained stable.

tuning optical properties of opal photonic crystals by structural defects engineering

We report on the preparation and optical characterization of three dimensional colloidal photonic crystal (PhC) containing an engineered planar defect embedding photoactive push-pull dyes. Free standing polystyrene films having thickness between 0.6 and 3 microns doped with different dipolar chromophores were prepared. These films were sandwiched between two artificial opals creating a PhC structure with planar defect. The system was characterized by reflectance at normal incidence angle (R), variable angle transmittance (T), and photoluminescence spectroscopy (PL). Clear evidence of defect states were observed in T and R spectra, which allow the light to propagate for selected frequencies within the pseudogap (stop band)

Nanoscale Assembly of Functional Peptides with Divergent Programming Elements

Self-assembling peptides are being applied both in the biomedical area and as building blocks in nanotechnology. Their applications are closely linked to their modes of self-assembly, which determine the functional nanostructures that they form. This work brings together two structural elements that direct nanoscale self-association in divergent directions: proline as a β-breaker and the β-structure-associated diphenylalanine motif, into a single tripeptide sequence. Amino acid chirality was found to resolve the tension inherent to these conflicting self-assembly instructions. Stereoconfiguration determined the ability of each of the eight possible Pro-Phe-Phe stereoisomers to self-associate into diverse nanostructures, including nanoparticles, nanotapes, or fibrils, which yielded hydrogels with gel-to-sol transition at a physiologically relevant temperature. Three single-crystal structures and all-atom molecular dynamics simulations elucidated the ability of each peptide to establish key interactions to form long-range assemblies (i,e., stacks leading to gelling fibrils), medium-range assemblies (i.e., stacks yielding nanotapes), or short-range assemblies (i.e., dimers or trimers that further associated into nanoparticles). Importantly, diphenylalanine is known to serve as a binding site for pathological amyloids, potentially allowing these heterochiral systems to influence the fibrillization of other biologically relevant peptides. To probe this hypothesis, all eight Pro-Phe-Phe stereoisomers were tested in vitro on the Alzheimer's disease-associated Aβ(1-42) peptide. Indeed, one nonfibril-forming stereoisomer effectively inhibited Aβ fibrillization through multivalent binding between diphenylalanine motifs. This work thus defined heterochirality as a useful feature to strategically develop future therapeutics to interfere with pathological processes, with the additional value of resistance to protease-mediated degradation and biocompatibility

Heterochirality and Halogenation Control Phe-Phe Hierarchical Assembly

Diphenylalanine is an amyloidogenic building block that can form a versatile array of supramolecular materials. Its shortcomings, however, include the uncontrolled hierarchical assembly into microtubes of heterogeneous size distribution and well-known cytotoxicity. This study rationalized heterochirality as a successful strategy to address both of these pitfalls and it provided an unprotected heterochiral dipeptide that self-organized into a homogeneous and optically clear hydrogel with excellent ability to sustain fibroblast cell proliferation and viability. Substitution of one l-amino acid with its d-enantiomer preserved the ability of the dipeptide to self-organize into nanotubes, as shown by single-crystal XRD analysis, whereby the pattern of electrostatic and hydrogen bonding interactions of the backbone was unaltered. The effect of heterochirality was manifested in subtle changes in the positioning of the aromatic side chains, which resulted in weaker intermolecular interactions between nanotubes. As a result, d-Phe-l-Phe self-organized into homogeneous nanofibrils with a diameter of 4 nm, corresponding to two layers of peptides around a water channel, and yielded a transparent hydrogel. In contrast with homochiral Phe-Phe stereoisomer, it formed stable hydrogels thermoreversibly. d-Phe-l-Phe displayed no amyloid toxicity in cell cultures with fibroblast cells proliferating in high numbers and viability on this biomaterial, marking it as a preferred substrate over tissue-culture plastic. Halogenation also enabled the tailoring of d-Phe-l-Phe self-organization. Fluorination allowed analogous supramolecular packing as confirmed by XRD, thus nanotube formation, and gave intermediate levels of bundling. In contrast, iodination was the most effective strategy to augment the stability of the resulting hydrogel, although at the expense of optical transparency and biocompatibility. Interestingly, iodine presence hindered the supramolecular packing into nanotubes, resulting instead into amphipathic layers of stacked peptides without the occurrence of halogen bonding. By unravelling fine details to control these materials at the meso- A nd macro-scale, this study significantly advanced our understanding of these systems

Stress detection using wearable physiological and sociometric sensors

Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detection of stress of people in a social situation by combining two sensor systems that capture physiological and social responses. We compare the performance using different classifiers including support vector machine, AdaBoost, and k-nearest neighbour. Our experimental results show that by combining the measurements from both sensor systems, we could accurately discriminate between stressful and neutral situations during a controlled Trier social stress test (TSST). Moreover, this paper assesses the discriminative ability of each sensor modality individually and considers their suitability for real time stress detection. Finally, we present an study of the most discriminative features for stress detection

A three-dimensional view of structural changes caused by deactivation of fluid catalytic cracking catalysts

Since its commercial introduction three-quarters of a century ago, fluid catalytic cracking has been one of the most important conversion processes in the petroleum industry. In this process, porous composites composed of zeolite and clay crack the heavy fractions in crude oil into transportation fuel and petrochemical feedstocks. Yet, over time the catalytic activity of these composite particles decreases. Here, we report on ptychographic tomography, diffraction, and fluorescence tomography, as well as electron microscopy measurements, which elucidate the structural changes that lead to catalyst deactivation. In combination, these measurements reveal zeolite amorphization and distinct structural changes on the particle exterior as the driving forces behind catalyst deactivation. Amorphization of zeolites, in particular, close to the particle exterior, results in a reduction of catalytic capacity. A concretion of the outermost particle layer into a dense amorphous silica–alumina shell further reduces the mass transport to the active sites within the composite