Sampling-based optimal kinodynamic planning with motion primitives

This paper proposes a novel sampling-based motion planner, which integrates in RRT* (Rapidly exploring Random Tree star) a database of pre-computed motion primitives to alleviate its computational load and allow for motion planning in a dynamic or partially known environment. The database is built by considering a set of initial and final state pairs in some grid space, and determining for each pair an optimal trajectory that is compatible with the system dynamics and constraints, while minimizing a cost. Nodes are progressively added to the tree {of feasible trajectories in the RRT* by extracting at random a sample in the gridded state space and selecting the best obstacle-free motion primitive in the database that joins it to an existing node. The tree is rewired if some nodes can be reached from the new sampled state through an obstacle-free motion primitive with lower cost. The computationally more intensive part of motion planning is thus moved to the preliminary offline phase of the database construction at the price of some performance degradation due to gridding. Grid resolution can be tuned so as to compromise between (sub)optimality and size of the database. The planner is shown to be asymptotically optimal as the grid resolution goes to zero and the number of sampled states grows to infinity

Weak nodes detection in urban transport systems: Planning for resilience in Singapore

The availability of massive data-sets describing human mobility offers the possibility to design simulation tools to monitor and improve the resilience of transport systems in response to traumatic events such as natural and man-made disasters (e.g. floods terroristic attacks, etc...). In this perspective, we propose ACHILLES, an application to model people's movements in a given transport system mode through a multiplex network representation based on mobility data. ACHILLES is a web-based application which provides an easy-to-use interface to explore the mobility fluxes and the connectivity of every urban zone in a city, as well as to visualize changes in the transport system resulting from the addition or removal of transport modes, urban zones, and single stops. Notably, our application allows the user to assess the overall resilience of the transport network by identifying its weakest node, i.e. Urban Achilles Heel, with reference to the ancient Greek mythology. To demonstrate the impact of ACHILLES for humanitarian aid we consider its application to a real-world scenario by exploring human mobility in Singapore in response to flood prevention.Comment: 9 pages, 6 figures, IEEE Data Science and Advanced Analytic

Object-oriented modelling of a flexible beam including geometric nonlinearities

In this paper, an efficient approach for the modelling and simulation of slender beams subject to heavy inertial loads is presented. The limitations imposed by a linear formulation of elasticity are overcome by a second order expansion of the displacement field, based on a geometrical exact beam model. In light of this, the nonlinearities of the elastic terms are shifted as inertial contributions, which yields an expression of the equations of motion in closed form. Thanks to the formulation in closed form, the proposed model is implemented in Modelica, with particular care to the suitability of the model with respect to the Modelica Multibody library. After describing the model formulation and implementation, the paper presents some simulation results, in order to validate the model with respect to benchmarks, widely adopted in literature

Abrasive waterjet intensifier model for machine diagnostics

This paper investigates the dynamics of a waterjet plant with multiple phased single-acting plungers. An object oriented dynamic model is proposed and discussed. The simulator may be tuned to generate signals under different health conditions to train multi-fault diagnosis tools. In fact, due to the challenging pressure conditions and the aggressiveness of abrasive materials, the reliability of machine tool components is a major concern. The information throughput provided by the model is validated with respect to real-industrial data, acquired in reference cutting scenarios

Walk-through programming for robotic manipulators based on admittance control

The present paper addresses the issues that should be covered in order to develop walk-through programming techniques (i.e. a manual guidance of the robot) in an industrial scenario. First, an exact formulation of the dynamics of the tool the human should feel when interacting with the robot is presented. Then, the paper discusses a way to implement such dynamics on an industrial robot equipped with an open robot control system and a wrist force/torque sensor, as well as the safety issues related to the walk-through programming. In particular, two strategies that make use of admittance control to constrain the robot motion are presented. One slows down the robot when the velocity of the tool centre point exceeds a specified safety limit, the other one limits the robot workspace by way of virtual safety surfaces. Experimental results on a COMAU Smart Six robot are presented, showing the performance of the walk-through programming system endowed with the two proposed safety strategies

Model based Detection and 3D Localization of Planar Objects for Industrial Setups

In this work we present a method to detect and estimate the three-dimensional pose of planar and textureless objects placed randomly on a conveyor belt or inside a bin. The method is based on analysis of single 2D images acquired by a standard camera. The algorithm exploits a template matching method to recognize the objects. A set of pose hypotheses are then refined and, based on a gradient orientation scoring, the best object to be manipulated is selected. The method is flexible and can be used with different objects without changing parameters since it exploits a CAD model as input for template generation. We validated the method using synthetic images. An experimental setup has been also designed using a fixed standard camera to localize planar metal objects in various scenarios

A Dedicated Tool for Presurgical Mapping of Brain Tumors and Mixed-Reality Navigation During Neurosurgery

Brain tumor surgery requires a delicate tradeoff between complete removal of neoplastic tissue while minimizing loss of brain function. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) have emerged as valuable tools for non-invasive assessment of human brain function and are now used to determine brain regions that should be spared to prevent functional impairment after surgery. However, image analysis requires different software packages, mainly developed for research purposes and often difficult to use in a clinical setting, preventing large-scale diffusion of presurgical mapping. We developed a specialized software able to implement an automatic analysis of multimodal MRI presurgical mapping in a single application and to transfer the results to the neuronavigator. Moreover, the imaging results are integrated in a commercially available wearable device using an optimized mixed-reality approach, automatically anchoring 3-dimensional holograms obtained from MRI with the physical head of the patient. This will allow the surgeon to virtually explore deeper tissue layers highlighting critical brain structures that need to be preserved, while retaining the natural oculo-manual coordination. The enhanced ergonomics of this procedure will significantly improve accuracy and safety of the surgery, with large expected benefits for health care systems and related industrial investors

Defective Function of the Fas Apoptotic Pathway in Type 1 Diabetes Mellitus Correlates with Age at Onset

The Fas death receptor triggers lymphocyte apoptosis through an extrinsic and an intrinsic pathway involving caspase-8 and -9 respectively. Inherited defects of Fas function are displayed by a proportion of patients with Type 1 diabetes mellitus (T1DM) especially those with a second autoimmunity (T1DM-p). This study assesses activation of both pathways in Fas-resistant (FasR) patients to localize the defect. 21/28 (75%) T1DM-p, 14/50 (38%) T1DM, and 7/150 (5%) controls were FasR. Analysis of the 35 FasR patients and 20 Fas-sensitive (FasS) controls showed that caspase-9 activity was lower in T1DM-p and T1DM than in controls, whereas caspase-8 activity was lower in T1DM-p than in T1DM and the controls. Single patient analysis showed that 16/35 patients displayed defective activity of one (FasR1), whereas 19 displayed normal activity of both caspases (FasR2) Ages at onset of diabetes mellitus in T1DM and the second autoimmune disease in T1DM-p were lower in FasR than in FasS patients. All FasR1 patients developed diabetes mellitus before the age of 9 years, whereas a later onset was displayed by 26% FasR2 and 53% FasS patients. These data show that defective Fas function may involve both the extrinsic and intrinsic pathway in T1DM and severity correlates with the precocity of the autoimmune attack and its tissue polyreactivity

Effects of Second Language Learning on the Plastic Aging Brain: Functional Connectivity, Cognitive Decline, and Reorganization

Learning a new language requires the use of extensive neural networks and can represent a powerful tool to reorganize brain neuroplasticity. In this study, we analyze how a 4 months long second language learning program (16, 2 h sessions) can lead to functional changes in the brain of healthy elderly individuals. A large number of studies point out a decline of brain-skills with age; here it is analyzed how cognition together with functional brain organization can be improved later in life. Twenty-six older adults (59–79 years old) were enrolled in the present study. A complete neuropsychological examination was administered before and after the intervention to measure global cognition levels, short- and long-term memory, attention, language access and executive functions. At the end of the program, in the intervention group, the results showed a significant improvement in global cognition together with an increased functional connectivity in the right inferior frontal gyrus (rIFG), right superior frontal gyrus (rSFG) and left superior parietal lobule (lSPL). These findings can be added to the current neurobiological breakthroughs of reshaping brain networks with a short language learning practice in healthy elderly subjects. Therefore, learning a foreign-language may represent a potentially helpful cognitive intervention for promoting healthy aging

A Neural “Tuning Curve” for Multisensory Experience and Cognitive-Perceptual Schizotypy

Our coherent perception of external events is enabled by the integration of inputs from different senses occurring within a range of temporal offsets known as the temporal binding window (TBW), which varies from person to person. A relatively wide TBW may increase the likelihood that stimuli originating from different environmental events are erroneously integrated and abnormally large TBW has been found in psychiatric disorders characterized by unusual perceptual experiences. Despite strong evidence of interindividual differences in TBW, both within clinical and nonclinical populations, the neurobiological underpinnings of this variability remain unclear. We adopted an integrated strategy linking TBW to temporal dynamics in functional magnetic resonance imaging (fMRI)-resting-state activity and cortical excitation/inhibition (E/I) balance, indexed by glutamate/Gamma-AminoButyric Acid (GABA) concentrations and common variation in glutamate and GABA genes in a healthy sample. Stronger resting-state longrange temporal correlations, indicated by larger power law exponent (PLE), in the auditory cortex, robustly predicted narrower audio-tactile TBW, which was in turn associated with lower cognitive-perceptual schizotypy. Furthermore, PLE was highest and TBW narrowest for individuals with intermediate levels of E/I balance, with shifts towards either extreme resulting in reduced multisensory temporal precision and increased schizotypy, effectively forming a neural ?tuning curve? for multisensory experience and schizophrenia risk. Our findings shed light on the neurobiological underpinnings of multisensory integration and its potentially clinically relevant inter-individual variability