Towards Orientation Learning and Adaptation in Cartesian Space

As a promising branch of robotics, imitation learning emerges as an important way to transfer human skills to robots, where human demonstrations represented in Cartesian or joint spaces are utilized to estimate task/skill models that can be subsequently generalized to new situations. While learning Cartesian positions suffices for many applications, the end-effector orientation is required in many others. Despite recent advances in learning orientations from demonstrations, several crucial issues have not been adequately addressed yet. For instance, how can demonstrated orientations be adapted to pass through arbitrary desired points that comprise orientations and angular velocities? In this article, we propose an approach that is capable of learning multiple orientation trajectories and adapting learned orientation skills to new situations (e.g., via-points and end-points), where both orientation and angular velocity are considered. Specifically, we introduce a kernelized treatment to alleviate explicit basis functions when learning orientations, which allows for learning orientation trajectories associated with high-dimensional inputs. In addition, we extend our approach to the learning of quaternions with angular acceleration or jerk constraints, which allows for generating smoother orientation profiles for robots. Several examples including experiments with real 7-DoF robot arms are provided to verify the effectiveness of our method

Generalized Orientation Learning in Robot Task Space

In the context of imitation learning, several approaches have been developed so as to transfer human skills to robots, with demonstrations often represented in Cartesian or joint space. While learning Cartesian positions suffices for many applications, the end-effector orientation is required in many others. However, several crucial issues arising from learning orientations have not been adequately addressed yet. For instance, how can demonstrated orientations be adapted to pass through arbitrary desired points that comprise orientations and angular velocities? In this paper, we propose an approach that is capable of learning multiple orientation trajectories and adapting learned orientation skills to new situations (e.g., via-point and end-point), where both orientation and angular velocity are addressed. Specifically, we introduce a kernelized treatment to alleviate explicit basis functions when learning orientations. Several examples including comparison with the state-of-the-art dynamic movement primitives are provided to verify the effectiveness of our method

Uncertainty-Aware Imitation Learning using Kernelized Movement Primitives

During the past few years, probabilistic approaches to imitation learning have earned a relevant place in the literature. One of their most prominent features, in addition to extracting a mean trajectory from task demonstrations, is that they provide a variance estimation. The intuitive meaning of this variance, however, changes across different techniques, indicating either variability or uncertainty. In this paper we leverage kernelized movement primitives (KMP) to provide a new perspective on imitation learning by predicting variability, correlations and uncertainty about robot actions. This rich set of information is used in combination with optimal controller fusion to learn actions from data, with two main advantages: i) robots become safe when uncertain about their actions and ii) they are able to leverage partial demonstrations, given as elementary sub-tasks, to optimally perform a higher level, more complex task. We showcase our approach in a painting task, where a human user and a KUKA robot collaborate to paint a wooden board. The task is divided into two sub-tasks and we show that using our approach the robot becomes compliant (hence safe) outside the training regions and executes the two sub-tasks with optimal gains.Comment: Published in the proceedings of IROS 201

A probabilistic framework for learning geometry-based robot manipulation skills

Programming robots to perform complex manipulation tasks is difficult because many tasks require sophisticated controllers that may rely on data such as manipulability ellipsoids, stiffness/damping and inertia matrices. Such data are naturally represented as Symmetric Positive Definite (SPD) matrices to capture specific geometric characteristics of the data, which increases the complexity of hard-coding them. To alleviate this difficulty, the Learning from Demonstration (LfD) paradigm can be used in order to learn robot manipulation skills with specific geometric constraints encapsulated in SPD matrices. Learned skills often need to be adapted when they are applied to new situations. While existing techniques can adapt Cartesian and joint space trajectories described by various desired points, the adaptation of motion skills encapsulated in SPD matrices remains an open problem. In this paper, we introduce a new LfD framework that can learn robot manipulation skills encapsulated in SPD matrices from expert demonstrations and adapt them to new situations defined by new start-, via- and end-matrices. The proposed approach leverages Kernelized Movement Primitives (KMPs) to generate SPD-based robot manipulation skills that smoothly adapt the demonstrations to conform to new constraints. We validate the proposed framework using a couple of simulations in addition to a real experiment scenario

The combination of a blood test and Fibroscan improves the non-invasive diagnosis of liver fibrosis

Background and aims: Blood tests and liver stiffness evaluation (LSE) by ultrasonographic elastometry are accurate tools for diagnosing liver fibrosis. We evaluated whether their synchronous combination in new scores could improve the diagnostic accuracy and reduce liver biopsy requirement in algorithm. Methods: Three hundred and ninety patients with chronic liver disease of miscellaneous causes were included. Five blood fibrosis tests were evaluated: APRI, FIB-4, Hepascore, Fibrotest and FibroMeter. The reference was fibrosis Metavir staging. Results: Diagnosis of significant fibrosis (Metavir F≥2). The most accurate synchronous combination was FibroMeter+LSE, which provided a significantly higher area under the receiver operating characteristic curve (0.892) than LSE alone (0.867, P=0.011) or Fibrometer (0.834, P<10−3). An algorithm using the FibroMeter+LSE combination and then a liver biopsy in indeterminate cases had 91.9% diagnostic accuracy and required significantly fewer biopsies (20.2%) than previously published Bordeaux algorithm (28.6%, P=0.02) or sequential algorithm for fibrosis evaluation (SAFE) (55.7%, P<10−3). The Angers algorithm performance was not significantly different between viral hepatitis and other causes. Diagnosis of cirrhosis. The most accurate synchronous combination was LSE+FibroMeter, which provided ≥90% predictive values for cirrhosis in 90.6% of patients vs 87.4% for LSE (P=0.02) and 57.9% for FibroMeter (P<10−3). An algorithm including the LSE+FibroMeter combination, and then a liver biopsy in indeterminate cases, had a significantly higher diagnostic accuracy than the SAFE algorithm (91.0 vs 79.8%, P<10−3), and required significantly fewer biopsies than the Bordeaux algorithm (9.3 vs 25.3%, P<10−3). Conclusion: The synchronous combination of a blood test plus LSE improves the accuracy of the non-invasive diagnosis of liver fibrosis and, consequently, markedly decreases the biopsy requirement in the diagnostic algorithm, notably to <10% in cirrhosis diagnosis

Exploiting Available Memory and Disk for Scalable Instant Overview Search

Abstract. Search-As-You-Type (or Instant Search) is a recently intro-duced functionality which shows predictive results while the user types a query letter by letter. In this paper we generalize and propose an ex-tension of this technique which apart from showing on-the-fly the first page of results, it shows various other kinds of information, e.g. the outcome of results clustering techniques, or metadata-based groupings of the results. Although this functionality is more informative than the classic search-as-you type, since it combines Autocompletion, Search-As-You-Type, and Results Clustering, the provision of real-time interaction is more challenging. To tackle this issue we propose an approach based on pre-computed information and we comparatively evaluate various in-dex structures for making real-time interaction feasible, even if the size of the available memory space is limited. This comparison reveals the mem-ory/performance trade-off and allows deciding which index structure to use according to the available main memory and desired performance. Furthermore we show that an incremental algorithm can be used to keep the index structure fresh.

One-pot hydrogen peroxide and hydrohalic acid induced ring closure and selective aromatic halogenation to give new ring-fused benzimidazoles

A new series of selectively dichlorinated and dibrominated five to eight-membered ring [1,2-a] fused benzimidazoles and [1,4]oxazino[4,3-a]benzimidazoles are synthesized in mostly high yields of >80% using the reaction of hydrogen peroxide and hydrohalic acid with commercially available o-cyclic amine substituted anilines. Domestic bleach with HCl is also capable of a one-pot ring-closure and chlorination

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

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

Global economic burden of unmet surgical need for appendicitis

Background: There is a substantial gap in provision of adequate surgical care in many low-and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods: Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results: Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion: For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially