A Hybrid Approach for Trajectory Control Design

This work presents a methodology to design trajectory tracking feedback control laws, which embed non-parametric statistical models, such as Gaussian Processes (GPs). The aim is to minimize unmodeled dynamics such as undesired slippages. The proposed approach has the benefit of avoiding complex terramechanics analysis to directly estimate from data the robot dynamics on a wide class of trajectories. Experiments in both real and simulated environments prove that the proposed methodology is promising.Comment: 9 pages, 11 figure

PLVS: A SLAM System with Points, Lines, Volumetric Mapping, and 3D Incremental Segmentation

This document presents PLVS: a real-time system that leverages sparse SLAM, volumetric mapping, and 3D unsupervised incremental segmentation. PLVS stands for Points, Lines, Volumetric mapping, and Segmentation. It supports RGB-D and Stereo cameras, which may be optionally equipped with IMUs. The SLAM module is keyframe-based, and extracts and tracks sparse points and line segments as features. Volumetric mapping runs in parallel with respect to the SLAM front-end and generates a 3D reconstruction of the explored environment by fusing point clouds backprojected from keyframes. Different volumetric mapping methods are supported and integrated in PLVS. We use a novel reprojection error to bundle-adjust line segments. This error exploits available depth information to stabilize the position estimates of line segment endpoints. An incremental and geometric-based segmentation method is implemented and integrated for RGB-D cameras in the PLVS framework. We present qualitative and quantitative evaluations of the PLVS framework on some publicly available datasets. The appendix details the adopted stereo line triangulation method and provides a derivation of the Jacobians we used for line error terms. The software is available as open-source

3D Multi-Robot Exploration with a Two-Level Coordination Strategy and Prioritization

This work presents a 3D multi-robot exploration framework for a team of UGVs moving on uneven terrains. The framework was designed by casting the two-level coordination strategy presented in [1] into the context of multi-robot exploration. The resulting distributed exploration technique minimizes and explicitly manages the occurrence of conflicts and interferences in the robot team. Each robot selects where to scan next by using a receding horizon next-best-view approach [2]. A sampling-based tree is directly expanded on segmented traversable regions of the terrain 3D map to generate the candidate next viewpoints. During the exploration, users can assign locations with higher priorities on-demand to steer the robot exploration toward areas of interest. The proposed framework can be also used to perform coverage tasks in the case a map of the environment is a priori provided as input. An open-source implementation is available online

Development and trade competitiveness of the European wine sector: A gravity analysis of intra-EU flows

AbstractThis study analyses the intra-EU trade of the world׳s chief wine exporters, namely Italy, France and Spain. Using an augmented version of the gravity model we empirically assess which of the three countries have experienced growth in intra-EU market trade. Effects of transportation costs, as well as demand and supply gaps between origin and destination countries, on the size of bilateral trade flows were specifically taken into account. Estimation results highlight the differences between bulk and bottled wine, providing useful information for European producers and policy-makers involved on regulation of wine sector. As concern bulk wine, Italy and Spain show no element of growth in competitiveness, while France shows a statistically significant annual decrease. In contrast, estimates for bottled wine all show a growth tendency, albeit with a different magnitude of coefficients. Italy is the country with the highest trend, followed by Spain and France which instead has a decidedly modest growth in export values. However, analysis of pricing policies shows that France does not appear to target an increase in export volumes so much as an increase in average unit price, while Italy, and especially Spain, have a tendency to increase export volumes, also to the detriment of prices

3D Localization, Mapping and Path Planning for Search and Rescue Operations

This work presents our results on 3D robot localization, mapping and path planning for the latest joint exercise of the European project 'Long-Term Human-Robot Teaming for Robots Assisted Disaster Response (TRADR). The full system is operated and evaluated by firemen end-users in real-world search and rescue experiments. We demonstrate that the system is able to plan a path to a goal position desired by the fireman operator in the TRADR Operational Control Unit (OCU), using a persistent 3D map created by the robot during previous sorties

Visual search and recognition for robot task execution and monitoring

Visual search of relevant targets in the environment is a crucial robot skill. We propose a preliminary framework for the execution monitor of a robot task, taking care of the robot attitude to visually searching the environment for targets involved in the task. Visual search is also relevant to recover from a failure. The framework exploits deep reinforcement learning to acquire a "common sense" scene structure and it takes advantage of a deep convolutional network to detect objects and relevant relations holding between them. The framework builds on these methods to introduce a vision-based execution monitoring, which uses classical planning as a backbone for task execution. Experiments show that with the proposed vision-based execution monitor the robot can complete simple tasks and can recover from failures in autonomy

Pandemic nightmares: effects on dream activity of the COVID-19 lockdown in Italy

COVID-19 has critically impacted the world. Recent works have found substantial changes in sleep and mental health during the COVID-19 pandemic. Dreams could give us crucial information about people's well-being, so here we have directly investigated the consequences of lockdown on the oneiric activity in a large Italian sample: 5,988 adults completed a web-survey during lockdown. We investigated sociodemographic and COVID-19-related information, sleep quality (by the Medical Outcomes Study-Sleep Scale), mental health (by the Depression, Anxiety, and Stress Scales), dream and nightmare frequency, and related emotional aspects (by the Mannheim Dream Questionnaire). Comparisons between our sample and a population-based sample revealed that Italians are having more frequent nightmares and dreams during the pandemic. A multiple logistic regression model showed the predictors of high dream recall (young age, female gender, not having children, sleep duration) and high nightmare frequency (young age, female gender, modification of napping, sleep duration, intrasleep wakefulness, sleep problem index, anxiety, depression). Moreover, we found higher emotional features of dream activity in workers who have stopped working, in people who have relatives/friends infected by or who have died from COVID-19 and in subjects who have changed their sleep habits. Our findings point to the fact that the predictors of high dream recall and nightmares are consistent with the continuity between sleep mentation and daily experiences. According to the arousal-retrieval model, we found that poor sleep predicts a high nightmare frequency. We suggest monitoring dream changes during the epidemic, and also considering the implications for clinical treatment and prevention of mental and sleep disorders

Poor Sleep Quality and Its Consequences on Mental Health During the COVID-19 Lockdown in Italy

Background: Coronavirus disease 2019 (COVID-19) seriously affected the whole of Italy. The extreme virulence and the speed of propagation resulted in restrictions and home confinement. This change was immediately perceived by people who found themselves exposed to feelings of uncertainty, fear, anger, stress, and a drastic change in the diurnal but above all nocturnal lifestyle. For these reasons, we aimed to study the quality of sleep and its connection to distress levels and to evaluate how lifestyle changed in the Italian population during the lockdown. Methods: By means of an Internet survey we recruited 6,519 adults during the whole of the COVID-19 lockdown (from March 10–1st phase to May 4–2nd phase). We investigated the sociodemographic and COVID-19-related information and assessed sleep quality using the Medical Outcomes Study–sleep scale (MOS-SS) and mental health with the short form of Depression, Anxiety, and Stress Scales–21 Items (DASS- 21). Multiple logistic regression model was used to evaluate the multivariate association between the dependent variable (good sleeper vs. poor sleeper) and all the variables that were significant in the univariate analysis. Results: A total of 3,562 (55.32%) participants reported poor sleep quality according to the MOS-Sleep Index II score. The multiple binary logistic regression results of poor sleepers revealed several risk factors during the outbreak restrictions: female gender, living in Central Italy, having someone close who died because of COVID-19, markedly changed sleep–wake rhythms characterized by earlier or postponed habitual bedtime, earlier habitual awakening time and reduced number of afternoon naps, and extremely severe levels of stress, anxiety, and depression. Conclusion: This is the first study designed to understand sleep quality and sleep habits during the whole of the lockdown period in the Italian population that provides more than 6,000 participants in a survey developed specifically for the health emergency related to COVID-19. Our study found that more than half of the Italian population had impaired sleep quality and sleep habits due to elevated psychological distress during the COVID- 19 lockdown containment measures. A multidisciplinary action should be undertaken in order to plan appropriate responses to the current crisis caused by the lockdown for the COVID-19 outbreak