Localizability Optimization for Multi Robot Systems and Applications to Ultra-Wide Band Positioning

RÉSUMÉ: RÉSUMÉ Les Systèmes Multi-Robots (SMR) permettent d’effectuer des missions de manière efficace et robuste du fait de leur redondance. Cependant, les robots étant des véhicules autonomes, ils nécessitent un positionnement précis en temps réel. Les techniques de localisation qui utilisent des Mesures Relatives (MR) entre les robots, pouvant être des distances ou des angles, sont particulièrement adaptées puisqu’elles peuvent bénéficier d’algorithmes coopératifs au sein du SMR afin d’améliorer la précision pour l’ensemble des robots. Dans cette thèse, nous proposons des stratégies pour améliorer la localisabilité des SMR, qui est fonction de deux facteurs. Premièrement, la géométrie du SMR influence fondamentalement la qualité de son positionnement pour des MR bruitées. Deuxièmement, les erreurs de mesures dépendent fortement de la technologie utilisée. Dans nos expériences, nous nous focalisons sur la technologie UWB (Ultra-Wide Band), qui est populaire pour le positionnement des robots en environnement intérieur en raison de son coût modéré et sa haute précision. Par conséquent, une partie de notre travail est consacrée à la correction des erreurs de mesure UWB afin de fournir un système de navigation opérationnel. En particulier, nous proposons une méthode de calibration des biais systématiques et un algorithme d’atténuation des trajets multiples pour les mesures de distance en milieu intérieur. Ensuite, nous proposons des Fonctions de Coût de Localisabilité (FCL) pour caractériser la géométrie du SMR, et sa capacité à se localiser. Pour cela, nous utilisons la Borne Inférieure de Cramér-Rao (BICR) en vue de quantifier les incertitudes de positionnement. Par la suite, nous fournissons des schémas d’optimisation décentralisés pour les FCL sous l’hypothèse de MR gaussiennes ou log-normales. En effet, puisque le SMR peut se déplacer, certains de ses robots peuvent être déployés afin de minimiser la FCL. Cependant, l’optimisation de la localisabilité doit être décentralisée pour être adaptée à des SMRs à grande échelle. Nous proposons également des extensions des FCL à des scénarios où les robots embarquent plusieurs capteurs, où les mesures se dégradent avec la distance, ou encore où des informations préalables sur la localisation des robots sont disponibles, permettant d’utiliser la BICR bayésienne. Ce dernier résultat est appliqué au placement d’ancres statiques connaissant la distribution statistique des MR et au maintien de la localisabilité des robots qui se localisent par filtrage de Kalman. Les contributions théoriques de notre travail ont été validées à la fois par des simulations à grande échelle et des expériences utilisant des SMR terrestres. Ce manuscrit est rédigé par publication, il est constitué de quatre articles évalués par des pairs et d’un chapitre supplémentaire. ABSTRACT: ABSTRACT Multi-Robot Systems (MRS) are increasingly interesting to perform tasks eÿciently and robustly. However, since the robots are autonomous vehicles, they require accurate real-time positioning. Localization techniques that use relative measurements (RMs), i.e., distances or angles, between the robots are particularly suitable because they can take advantage of cooperative schemes within the MRS in order to enhance the precision of its positioning. In this thesis, we propose strategies to improve the localizability of the SMR, which is a function of two factors. First, the geometry of the MRS fundamentally influences the quality of its positioning under noisy RMs. Second, the measurement errors are strongly influenced by the technology chosen to gather the RMs. In our experiments, we focus on the Ultra-Wide Band (UWB) technology, which is popular for indoor robot positioning because of its mod-erate cost and high accuracy. Therefore, one part of our work is dedicated to correcting the UWB measurement errors in order to provide an operable navigation system. In particular, we propose a calibration method for systematic biases and a multi-path mitigation algorithm for indoor distance measurements. Then, we propose Localizability Cost Functions (LCF) to characterize the MRS’s geometry, using the Cramér-Rao Lower Bound (CRLB) as a proxy to quantify the positioning uncertainties. Subsequently, we provide decentralized optimization schemes for the LCF under an assumption of Gaussian or Log-Normal RMs. Indeed, since the MRS can move, some of its robots can be deployed in order to decrease the LCF. However, the optimization of the localizability must be decentralized for large-scale MRS. We also propose extensions of LCFs to scenarios where robots carry multiple sensors, where the RMs deteriorate with distance, and finally, where prior information on the robots’ localization is available, allowing the use of the Bayesian CRLB. The latter result is applied to static anchor placement knowing the statistical distribution of the MRS and localizability maintenance of robots using Kalman filtering. The theoretical contributions of our work have been validated both through large-scale simulations and experiments using ground MRS. This manuscript is written by publication, it contains four peer-reviewed articles and an additional chapter

Synchronisation et positionnement simultanés d'un réseau ultra-large bande et applications en robotique mobile

RÉSUMÉ Il est essentiel pour les robots mobiles de pouvoir se localiser précisément dans leur environ-nement. Pour créer des estimateurs de position précis, il est nécessaire de disposer de mesures externes au robot, l’exemple le plus populaire étant les mesures GPS. Pour des applications en intérieur, nous ne pouvons raisonnablement pas utiliser des mesures satellitaires, pour des raisons de précision et de réception du signal. Dans ce mémoire, nous nous intéressons à la technologie radio UWB (Ultra Wide Band, c’est-à-dire Ultra-Large Bande), permettant de mesurer des distances entre agents dans un espace rapproché avec une précision de l’ordre de la dizaine de centimètres. Les techniques de localisation TOF utilisent le temps de vol (Time Of Flight) des ondes afin de mesurer les distances, en supposant que leur vitesse, uniforme, est celle de la lumière dans le vide. La mesure de distance est donc obtenue en multipliant le TOF par cette cette dernière. Pour cette raison, il est nécessaire d’obtenir une mesure de TOF avec une haute précision, typiquement de l’ordre de la nanoseconde. Cette contrainte est à respecter pour créer des estimateurs de position précis, afin d’estimer de manière adéquate le phénomène de dérive des horloges des divers agents du réseau. Des techniques, dites de Two Way Ranging (TWR), font une compensation par soustraction de cette dérive, faisant émettre des messages aux agents présents sur les robots, appelés les «tags» et des balises à position fixes connues appelées «ancres». En vertu de cette compen-sation, ces techniques ne nécessitent pas la mise en œuvre d’algorithmes de synchronisation pour les tags. Toutefois, elles ne permettent la localisation que d’un nombre restreint de robots, en raison du fait que les tags émettent de l’information. Motivés par les applications de systèmes multi-robots, nous élaborons dans de ce mémoire un protocole où les tags ne seront que récepteurs afin de pouvoir en localiser un plus grand nombre. Ceci nécessite une synchronisation précise des horloges du réseau d’ancres. Notre principale contribution est d’intégrer simultanément la synchronisation des ancres et l’esti-mation de position des tags dans un protocole basé sur des estimateurs de Kalman. Nous évaluons expérimentalement la performance de notre protocole dans des implémenta-tions de ce dernier qui utilisent des microcontrôleurs, capteurs, robots et logiciels populaires en robotique. Nous abordons aussi des développements dans le rejet de valeurs erratiques sur les mesures pourvues par les agents UWB. Notre protocole est également intégré dans des estimateurs utilisant des techniques de fusion de données de capteurs.----------ABSTRACT Mobile robots require accurate real-time location estimates to operate. These estimates use external measurements, obtained for example from Global Navigation Satellite Systems (GNSS), to correct integration errors from proprioceptive sensors. This master’s thesis fo-cuses on short-range Ultra-Wide Band (UWB) radios as a source of external range mea-surements, which can be used to provide centimeter-level positioning accuracy in indoor environments, where GNSS signals are generally unavailable. UWB-aided positioning systems most commonly rely on pseudorange measurements obtained by multiplying the speed of light by the Time-of-Flight (ToF) of messages transmitted be-tween UWB nodes with known positions, called anchors, and UWB nodes to localize, called tags. To achieve the localization accuracy desired for indoor applications, errors in ToF mea-surements need to remain below the nanosecond. The main challenge in achieving this level of accuracy comes from the fact that internal clocks at di˙erent nodes are not synchronized. Simple two-way ranging protocols can provide ToF measurements without synchronizing the nodes, but require the tags to transmit messages to the limited number of anchors and as a result do not support more than a few tags. Hence, motivated by applications requiring the deployment of multi-robot systems, we focus on one-way ranging protocols with the tags operating as passive receivers, which however requires synchronized anchors. The main con-tribution of this thesis is to design a protocol based on Kalman filtering to simultaneously synchronize UWB nodes and obtain ToF measurements between active anchors and passive tags. The modeling and rejection of outliers in these measurements is discussed in details in order to improve the robustness and performance of the proposed algorithm. The pseu-dorange measurements are also fused with other sensor measurements to design UWB-aided integrated navigation systems. Our algorithms are implemented on a custom embedded platform combining a commercial o˙-the-shelf micro-controller and UWB radio with inertial sensors, and interfaced with a standard software framework for robotics. We characterize the localization performance achievable in practice through several indoor experiments with ground robots

Empathic and Nonempathic Interaction in Chronic Pain Couples

Empathy and empathic response are receiving greater attention in pain research as investigators acknowledge that other forms of interaction may impact the pain process. The purpose of this study was to examine validation and invalidation as forms of empathic and nonempathic responses in chronic pain couples. Participants were 92 couples in which at least one spouse reported chronic musculoskeletal pain. Each couple participated in two videotaped interactions about the ways in which the pain has impacted their lives together. Trained raters then coded interactions for each partner’s use of validation and invalidation. Couples also completed surveys on spouse responses to pain, marital satisfaction, and perceived spousal support. Correlations demonstrated validation by spouses of persons with pain was associated with punishing, solicitous, and distracting spouse responses to pain, marital satisfaction, and perceived spousal support. In contrast, spouses’ invalidation scores were correlated with punishing spouse responses. Exploratory factor analyses were then conducted to determine the extent to which spouses’ responses to pain and spouse validation and invalidation loaded on similar factors. Results indicated that validation and invalidation are more closely related to punishing spouse responses than to solicitous or distracting spouse responses. These results have implications for theoretical and clinical work on spouse responding

Clock and Power-Induced Bias Correction for UWB Time-of-Flight Measurements

Ultra-Wide Band (UWB) communication systems can be used to design low cost, power efficient and precise navigation systems for mobile robots, by measuring the Time of Flight (ToF) of messages traveling between on-board UWB transceivers to infer their locations. Theoretically, decimeter level positioning accuracy or better should be achievable, at least in benign propagation environments where Line-of-Sight (LoS) between the transceivers can be maintained. Yet, in practice, even in such favorable conditions, one often observes significant systematic errors (bias) in the ToF measurements, depending for example on the hardware configuration and relative poses between robots. This letter proposes a ToF error model that includes a standard transceiver clock offset term and an additional term that varies with the received signal power (RxP). We show experimentally that, after fine correction of the clock offset term using clock skew measurements available on modern UWB hardware, much of the remaining pose dependent error in LoS measurements can be captured by the (appropriately defined) RxP-dependent term. This leads us to propose a simple bias compensation scheme that only requires on-board measurements (clock skew and RxP) to remove most of the observed bias in LoS ToF measurements and reliably achieve cm-level ranging accuracy. Because the calibrated ToF bias model does not depend on any extrinsic information such as receiver distances or poses, it can be applied before any additional error correction scheme that requires more information about the robots and their environment

GRAPE for fast and scalable graph processing and random-walk-based embedding

Graph representation learning methods opened new avenues for addressing complex, real-world problems represented by graphs. However, many graphs used in these applications comprise millions of nodes and billions of edges and are beyond the capabilities of current methods and software implementations. We present GRAPE (Graph Representation Learning, Prediction and Evaluation), a software resource for graph processing and embedding that is able to scale with big graphs by using specialized and smart data structures, algorithms, and a fast parallel implementation of random-walk-based methods. Compared with state-of-the-art software resources, GRAPE shows an improvement of orders of magnitude in empirical space and time complexity, as well as competitive edge- and node-label prediction performance. GRAPE comprises approximately 1.7 million well-documented lines of Python and Rust code and provides 69 node-embedding methods, 25 inference models, a collection of efficient graph-processing utilities, and over 80,000 graphs from the literature and other sources. Standardized interfaces allow a seamless integration of third- party libraries, while ready-to-use and modular pipelines permit an easy-to- use evaluation of graph-representation-learning methods, therefore also positioning GRAPE as a software resource that performs a fair comparison between methods and libraries for graph processing and embedding

The HAND-Q : Psychometrics of a New Patient-reported Outcome Measure for Clinical and Research Applications

Background: The perspective of the patient in measuring the outcome of their hand treatment is of key importance. We developed a hand-specific patient-reported outcome measure to provide a means to measure outcomes and experiences of care from the patient perspective, that is, HAND-Q. Methods: Data were collected from people with a broad range of hand conditions in hand clinics in six countries between April 2018 and January 2021. Rasch measurement theory analysis was used to perform item reduction and to examine reliability and validity of each HAND-Q scale. Results: A sample of 1277 patients was recruited. Participants ranged in age from 16 to 89 years, 54% were women, and a broad range of congenital and acquired hand conditions were represented. Rasch measurement theory analysis led to the refinement of 14 independently functioning scales that measure hand appearance, health-related quality of life, experience of care, and treatment outcome. Each scale evidenced reliability and validity. Examination of differential item functioning by age, gender, language, and type of hand condition (ie, nontraumatic versus traumatic) confirmed that a common scoring algorithm for each scale could be implemented. Conclusions: The HAND-Q was developed following robust psychometric methods to provide a comprehensive modular independently functioning set of scales. HAND-Q scales can be used to assess and compare evidence-based outcomes in patients with any type of hand condition.Peer reviewe

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

Genome sequence of the necrotrophic plant pathogen Pythium ultimum reveals original pathogenicity mechanisms and effector repertoire

Background: Pythium ultimum (P. ultimum) is a ubiquitous oomycete plant pathogen responsible for a variety of diseases on a broad range of crop and ornamental species. Results: The P. ultimum genome (42.8 Mb) encodes 15,290 genes and has extensive sequence similarity and synteny with related Phytophthora species, including the potato blight pathogen Phytophthora infestans. Whole transcriptome sequencing revealed expression of 86% of genes, with detectable differential expression of suites of genes under abiotic stress and in the presence of a host. The predicted proteome includes a large repertoire of proteins involved in plant pathogen interactions although surprisingly, the P. ultimum genome does not encode any classical RXLR effectors and relatively few Crinkler genes in comparison to related phytopathogenic oomycetes. A lower number of enzymes involved in carbohydrate metabolism were present compared to Phytophthora species, with the notable absence of cutinases, suggesting a significant difference in virulence mechanisms between P. ultimum and more host specific oomycete species. Although we observed a high degree of orthology with Phytophthora genomes, there were novel features of the P. ultimum proteome including an expansion of genes involved in proteolysis and genes unique to Pythium. We identified a small gene family of cadherins, proteins involved in cell adhesion, the first report in a genome outside the metazoans. Conclusions: Access to the P. ultimum genome has revealed not only core pathogenic mechanisms within the oomycetes but also lineage specific genes associated with the alternative virulence and lifestyles found within the pythiaceous lineages compared to the Peronosporaceae

Mosaic: A Satellite Constellation to Enable Groundbreaking Mars Climate System Science and Prepare for Human Exploration

The Martian climate system has been revealed to rival the complexity of Earth\u27s. Over the last 20 yr, a fragmented and incomplete picture has emerged of its structure and variability; we remain largely ignorant of many of the physical processes driving matter and energy flow between and within Mars\u27 diverse climate domains. Mars Orbiters for Surface, Atmosphere, and Ionosphere Connections (MOSAIC) is a constellation of ten platforms focused on understanding these climate connections, with orbits and instruments tailored to observe the Martian climate system from three complementary perspectives. First, low-circular near-polar Sun-synchronous orbits (a large mothership and three smallsats spaced in local time) enable vertical profiling of wind, aerosols, water, and temperature, as well as mapping of surface and subsurface ice. Second, elliptical orbits sampling all of Mars\u27 plasma regions enable multipoint measurements necessary to understand mass/energy transport and ion-driven escape, also enabling, with the polar orbiters, dense radio occultation coverage. Last, longitudinally spaced areostationary orbits enable synoptic views of the lower atmosphere necessary to understand global and mesoscale dynamics, global views of the hydrogen and oxygen exospheres, and upstream measurements of space weather conditions. MOSAIC will characterize climate system variability diurnally and seasonally, on meso-, regional, and global scales, targeting the shallow subsurface all the way out to the solar wind, making many first-of-their-kind measurements. Importantly, these measurements will also prepare for human exploration and habitation of Mars by providing water resource prospecting, operational forecasting of dust and radiation hazards, and ionospheric communication/positioning disruptions

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博士（学術）神戸大