ROBI’: A prototype mobile manipulator for agricultural applications

The design of ROBI', a prototype mobile manipulator for agricultural applications devised following low-cost, low-weight, simplicity, flexibility and modularity requirements, is presented in this work. The mechanical design and the selection of the main components of the motion control system, including sensors and in-wheel motors, is described. The kinematic and dynamic models of the robot are also derived, with the aim to support the design of a trajectory tracking system and to make a preliminary assessment of the design choices, as well. Finally, two simulations, one~specifically related to a realistic trajectory in an agricultural field, show the validity of these choices

Spatial-Relational Learning and Memory Deficits Associated with NMDAR Autoantibodies in Systemic Lupus Erythematosus

Individuals with Systemic Lupus Erythematosus (SLE) experience inflammation that may target any organ within the body, including the central and peripheral nervous systems. Additionally, these individuals often demonstrate psychological dysfunctions including emotional and cognitive deficits; however, research is inconsistent as to the nature and cause of these dysfunctions. While there are multiple factors that may increase risk for variability in cognitive function, such as population differences, socioeconomic status (SES), mood disorders (depression and anxiety), medication effects, and disease activity, these factors do not reliably predict the severity and extent of cognitive deficits. A growing body of animal research associates autoantibodies (Abs) in SLE with cognitive impairment. A specific Ab that targets N- methyl-D-aspartate receptors (NMDAR) and neuronal DNA, referred to as DNRAb, is associated with hippocampal damage and spatial memory deficits in mice. The goal of this project was to examine the relationship between the DNRAb and cognitive deficits specific to spatial-relational learning and memory within a sample of SLE patients. Two cohorts of healthy controls (HCs) and SLE patients were recruited. Cohort A included 33 HCs and 39 SLE participants (23 DNRAb-, 11 DNRAb+, 5 unknown Ab status). Cohort B included 11 HCs and 21 SLE participants (11 DNRAb-, 10 DNRAb+). All participants completed measures of emotional functioning and neuropsychological measures of visuospatial learning and memory, processing speed, and executive function. Cognitive testing of spatial memory and relational learning was evaluated by two laboratory-developed computerized tasks. Antibody status was determined after participants were recruited in the study. Overall, compared to SLE patients, HCs were significantly more accurate, and thus had better performance on the Spatial Memory and Relational Learning Tasks. The DNRAb+ group was significantly less accurate than HC on both computerized measures. However, the DRNAb- did not differ from either groups on the Spatial Memory Task, and performed similarly to the DRNAb+ group on the Relational Learning Task. This work provides a foundation for future research to analyze how SLE and Ab status could influence cognitive functioning. Future studies can continue to examine subtle cognitive deficits in SLE, consider the possibility of other brain areas to compensate for cognitive deficits in SLE, and provide additional breakthroughs to guide interventions for SLE patients

Towards Safe Human-Robot Interaction: evaluating in real-time the severity of possible collisions in industrial scenarios

It is today a common opinion that a more structured and fruitful human-robot cooperation will facilitate industrial robots to be massively used also in SMEs. In order to guarantee a certain level of safety while removing physica

Hepatic Steatosis and Thyroid Function Tests in Overweight and Obese Children

Objectives. Associations between thyroid function and nonalcoholic fatty liver disease (NAFLD) are unknown in childhood. Thus, the aim of the present study was to investigate in 402 consecutive overweight/obese children the association between thyroid function tests and hepatic steatosis as well as metabolic variables. Methods. Hepatic steatosis was diagnosed by ultrasound after exclusion of infectious and metabolic disorders. Fasting serum samples were taken for determination of thyroid function (TSH, FT4, and FT3), along with alanine aminotransferase (ALT), lipid profile, glucose, insulin, and insulin resistance (IR). Results. Eighty-eight children (21.9%) had TSH above the normal range (>4.0 mIU/L). FT3 and FT4 were within the reference intervals in all subjects. Elevated TSH was associated with increased odds of having hepatic steatosis (OR 2.10 (95% CI, 1.22–3.60)), hepatic steatosis with elevated ALT (2.42 (95% CI, 1.29–4.51)), hypertriglyceridemia, elevated total cholesterol, and IR as well as metabolic syndrome (considered as a single clinical entity), after adjustment for age, gender, pubertal status, and body mass index-SD score (or waist circumference). Conclusions. In overweight/obese children, elevated TSH concentration is a significant predictor of hepatic steatosis and lipid and glucose dysmetabolism, independently of the degree of total and visceral obesity

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

Investigation of multi-phase tubular permanent magnet linear generator for wave energy converters

In this article, an investigation into different magnetization topologies for a long stator tubular permanent magnet linear generator is performed through a comparison based on the cogging force disturbance, the power output, and the cost of the raw materials of the machines. The results obtained from finite element analysis simulation are compared with an existing linear generator described in [1]. To ensure accurate results, the generator developed in [1] is built with 3D CAD and simulated using the finite-element method, and the obtained results are verified with the source.The PRIMaRE project

A planner for All-Terrain Vehicles on unknown rough terrains based on the MPC paradigm and D*-like algorithm

A novel conceptual design of a planner for a mobile vehicle, operating on poorly traversable unknown rough terrains, is discussed. Finding a way to include a vehicle model into the planning stage, while coping with unknown or partially known terrains, is a challenging and rarely addressed optimization setup. The main advantages of a possible solution of such a problem would be twofold. First, the planner would give trajectories which are feasible to follow by the vehicle, which is not the case in many other state of the art planning algorithms especially for large vehicle speeds. Second, those trajectories would be the optimal ones in accordance to the current vehicle states and knowledge on its environment. We propose a solution based on an MPC planning paradigm, wherein the planner solves a constrained optimal control problem at each time instant using the current knowledge on the terrain, which is caught appropriately by an objective function. Solving an optimal control problem allows for the vehicle model being included into the planning stage, while the repeated optimization allows for taking continuously into account new terrain information. To deal with the information given beyond the sensor range and to guarantee reaching a given goal position, we have adopted a D∗-like algorithm for rough terrains being used as a cost-to-go term within the optimization setup

An incremental approach to learning generalizable robot tasks from human demonstration

Dynamic Movement Primitives (DMPs) are a common method for learning a control policy for a task from demonstration. This control policy consists of differential equations that can create a smooth trajectory to a new goal point. However, DMPs only have a limited ability to generalize the demonstration to new environments and solve problems such as obstacle avoidance. Moreover, standard DMP learning does not cope with the noise inherent to human demonstrations. Here, we propose an approach for robot learning from demonstration that can generalize noisy task demonstrations to a new goal point and to an environment with obstacles. This strategy for robot learning from demonstration results in a control policy that incorporates different types of learning from demonstration, which correspond to different types of observational learning as outlined in developmental psychology

Anti-collision systems for robotic applications based on laser Time-Of-Flight sensors

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