23 research outputs found

    Human-robot contactless collaboration with mixed reality interface

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    A control system based on multiple sensors is proposed for the safe collaboration of a robot with a human. New constrained and contactless human-robot coordinated motion tasks are defined to control the robot end-effector so as to maintain a desired relative position to the human head while pointing at it. Simultaneously, the robot avoids any collision with the operator and with nearby static or dynamic obstacles, based on distance compu- tations performed in the depth space of a RGB-D sensor. The various tasks are organized with priorities and executed under hard joint bounds using the Saturation in the Null Space (SNS) algorithm. A direct human-robot communication is integrated within a mixed reality interface using a stereo camera and an augmented reality system. The proposed system is significant for on-line, collaborative quality assessment phases in a manu- facturing process. Various experimental validation scenarios using a 7-dof KUKA LWR4 robot are presented

    Task Priority Matrix Under Hard Joint Constraints

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    We propose an extension to the Task Priority Matrix (TPM) method for redundancy resolution that includes also hard inequality joint constraints. This is done by combining TPM with a modified version of the basic Saturation in the Null Space (SNS) algorithm. Comparative simulations are reported for the 21-DOFs Romeo humanoid robot

    Motion Control of Redundant Robots with Generalised Inequality Constraints

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    We present an improved version of the Saturation in the Null Space (SNS) algorithm for redundancy resolution at the velocity level. In addition to hard bounds on joint space motion, we consider also Cartesian box constraints that cannot be violated at any time. The modified algorithm combines all bounds into a single augmented generalised vector and gives equal, highest priority to all inequality constraints. When needed, feasibility of the original task is enforced by the SNS task scaling procedure. Simulation results are reported for a 6R planar robot

    Kinematic control of redundant robots with online handling of variable generalized hard constraints

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    We present a generalized version of the Saturation in the Null Space (SNS) algorithm for the task control of redundant robots when hard inequality constraints are simultaneously present both in the joint and in the Cartesian space. These hard bounds should never be violated, are treated equally and in a unified way by the algorithm, and may also be varied, inserted or deleted online. When a joint/Cartesian bound saturates, the robot redundancy is exploited to continue fulfilling the primary task. If no feasible solution exists, an optimal scaling procedure is applied to enforce directional consistency with the original task. Simulation and experimental results on different robotic systems demonstrate the efficiency of the approach. The proposed algorithm can be viewed as a generic platform that is easily applicable to any robotic application in which robots operate in an unstructured environment and online handling of joint and Cartesian constraints is critical.Comment: 8 pages, 10 figures. This work has been submitted to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022 with RA-L option) for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

    Autoimmune Diseases of the GI Tract Part II: Emergence of Diagnostic Tools and Treatments

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    Autoimmune diseases (AD) have emerged as a pandemic in our modern societies, especially after the World War II. In part I, we have reviewed five main diseases and shed light on different aspects from introducing the concept of autoimmunity, the description of the disease’s pathogenesis and the diagnosis, the role of antibodies as markers for the prediction of the disease, the link between the gut and brain through what is known as the gut–brain axis, and the relationship of this axis in GI autoimmune diseases. In this chapter, we review the role of antibodies as markers for the prediction of the disease, artificial intelligence in GI autoimmune diseases, the nutritional role and implications in the five GI autoimmune diseases, and finally the treatment of those diseases

    Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

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    BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

    Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

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    Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

    Multi-sensor coordination in human-robot interaction

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    In the framework of Human-Robot interaction, a robot and a human operator may need to move in close coordination within the same workspace. In this thesis, the contactless human-robot collaboration with coordinated motion tasks is considered. A control system based on multiple sensors is presented for safe and efficient collaboration. A contactless coordinated motion can be achieved using vision, mounting a camera either on the robot end-effector or on the human. We consider here a visual coordination task, with the robot end-effector that should maintain a prescribed position with respect to a moving RGB-D camera while pointing at it. For the 3D localization of the moving camera, we compare three different techniques and introduce some improvements to the best solution found for our application. Instead, an Oculus Rift HMD system can be used to track an operator moving in the workspace. In this case, a stereo camera is used to perform a mixed-reality interface that enables the user to choose between different collaboration modes. The robot should also avoid any collision with the operator and with nearby static or dynamic obstacles, based on distance computations performed in the depth space of a fixed Kinect sensor. To exploit effectively and efficiently the advantage of robot redundancy, different soft constraints for both the coordinated motion and collision avoidance tasks are proposed. Two relaxed versions of the pointing part of the task are introduced to achieve the desired task without exhausting the robot capabilities. Also, a relaxed formulation for collision avoidance task, that does not slack the avoidance performance, is used. Several control algorithms with different complexity are developed to suitably combine and organize the simultaneous control tasks with their priority. The proposed control system using different approaches is validated by V-REP and MATLAB simulations, and experiments with the 7-dof KUKA LWR manipulator

    Multi-sensor control system for safe human-robot collaboration

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    In the framework of Human-Robot Collaboration, a robot and a human operator may need to move in close coordination within the same workspace. A contactless coordinated motion can be achieved using sensors to localize the human in the robot workspace. The robot end-effector should maintain a prescribed position with respect to the head of a moving human while pointing at it. At the same time, the robot should avoid collisions with the operator or with any other nearby obstacles. In this work, we propose a multi-sensor control system that handles these objectives efficiently in real time
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