128 research outputs found

    Treating Image Loss by Using the Vision/Motion Link:

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    Control of a magnetic microrobot navigating in microfluidic arterial bifurcations through pulsatile and viscous flow

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    International audienceNavigating in bodily fluids to perform targeted diagnosis and therapy has recently raised the problem of robust control of magnetic microrobots under real endovascular conditions. Various control approaches have been proposed in the literature but few of them have been experimentally validated. In this paper, we point out the problem of navigation controllability of magnetic microrobots in high viscous fluids and under pulsatile flow for endovascular applications. We consider the experimental navigation along a desired trajectory, in a simplified millimeter-sized arterial bifurcation, operating in fluids at the low-Reynolds-number regime where viscous drag significantly dominates over inertia. Different viscosity environments are tested (ranging from 100\% water-to-100\% glycerol) under a systolic pulsatile flow compatible with heart beating. The control performances in terms tracking, robustness and stability are then experimentally demonstrated

    Evaluation of Telerobotic Shared Control Strategy for Efficient Single-Cell Manipulation

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    International audienceMicroinjection is a method for the delivery of exogenous materials into cells and is widely used in biomedical research areas such as transgenics and genomics. However, this direct injection is a time-consuming and laborious task, resulting in low throughput and poor reproducibility. Here, we describe a telerobotic shared control framework for microinjection, in which a micromanipulator is controlled by the shared motion commands of both the human operator and the autonomous controller. To determine the weightings between the operator and the controller, we proposed a quantitative evaluation method using a model of speed/accuracy trade-offs in human movement. The results showed that a 40%-60% weighting on the human operator (or the controller) produced the best performance for both speed and accuracy of guiding and targeting task in microinjection suggesting that some level of both automation and human involvement is important for microinjection tasks

    Expert recommendations for the design of a children’s movement competence assessment tool for use by primary school teachers

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    A child’s early school years provide a crucial platform for them to develop fundamental movement skills (FMS), yet it has been acknowledged that there is a shortage of suitable FMS assessment tools for teachers to use within schools. To begin to address this shortfall, the purpose of this study was to elicit expert recommendations for the design of a FMS assessment tool for use by primary school teachers. A multi-phase research design was used, involving two scenario-guided focus groups with movement experts (n = 8; five academics and three practitioners). Data captured in both focus groups were transcribed verbatim and thematically analysed. Three dichotomous dilemmas emerged from the data in relation to assessing children’s movement competence: (a) Why? For research purposes or to enhance teaching and learning?; (b) How? Should the assessment setting be engineered or natural?; and (c) What? Should the detail of the assessment be complex or simple and should the nature of the tasks be static or dynamic? These findings suggest that any future development of movement competence assessment protocols for use by primary school teachers needs to consider the specific purpose and context of the assessment

    Microrobots magnétiques pour des applications biomédicales: Modélisation, simulation, contrôle et validations

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    This research work mainly focuses on the study of the modeling and control of microrobotic systems in a biomedical context. So far, the use of magnetic actuation has been regarded as the most convenient approach for such achievements. Besides, the cardiovascular system allows to reach most parts of the human body and is then chosen as the main navigation route. This original topic is a rapidly expanding field whose ambition is to modernize current therapies by trying to improve therapeutic targeting while improving patient comfort. To achieve this goal, a good understanding of how microrobots evolve in the human body is an important step. The theoretical foundations and the physical laws that make it possible to describe the various phenomena which act on magnetic microrobots in vascular-like environments have thus been deeply studied. Methodologies for dealing with multiphysics approaches combining different sources of hypotheses and uncertainties have been developed. Great care has been taken in their validations by experimentation when possible, otherwise by numerical analysis. This helps to better understand the dominant dynamics, as well as the predominant parameters in the description of magnetic microrobots in a vascular-like environment. This makes it possible to efficiently characterize and predict their behaviors in a viscous flow and their responses to magnetic fields. On this basis, advanced navigation strategies have been developed. The navigation process can be divided into two stages. First, safe and efficient navigation paths are planned (off-line) based on the fast marching method (FMM). With the proposed navigation planning framework, different constraints and objectives can then be taken into account to obtain a truly feasible reference path. Second, control schemes that drive the magnetic microrobots along the planned reference path to the targeted location are synthesized. To do so, predictive and optimal control laws have been implemented. All the proposed models and navigation strategies have been evaluated through various experiments under different conditions with the platforms developed at the PRISME Laboratory.Ce travail traite principalement l'étude de la modélisation et du contrôle de systèmes microrobotiques dans un contexte biomédical. Jusqu'à présent, l'utilisation de l'actionnement magnétique est considérée comme l'approche la plus prometteuse pour de telles réalisations. Par ailleurs, le système cardiovasculaire permet d'atteindre la plupart des parties du corps humain et est alors choisi comme voie de navigation principale. Cette thématique originale est un domaine en pleine expansion dont l'ambition est de moderniser les thérapies actuelles en essayant d'améliorer le ciblage thérapeutique tout en améliorant le confort des patients. Pour atteindre cet objectif, une bonne compréhension du comportement des microrobots dans le corps humain est une étape importante. Les fondements théoriques et les lois de la physique permettant de décrire les différents phénomènes qui agissent sur les microrobots magnétiques dans des environnements de type vasculaire ont ainsi été étudiés en détails. Des méthodologies pour traiter des approches multiphysiques combinant différentes sources d'hypothèses et d'incertitudes ont été développées. Un grand soin a été apporté à leurs validations par l'expérimentation lorsque cela était possible, le cas échéant par des analyses numériques. Cela permet de mieux comprendre la dynamique dominante, ainsi que les paramètres prédominants dans la description des microrobots magnétiques. Cela permet de caractériser et de prédire efficacement leurs comportements dans un écoulement visqueux et leurs réponses aux champs magnétiques. Sur cette base, des stratégies de navigation avancées ont été développées. Le processus de navigation peut être divisé en deux étapes. Premièrement, des chemins de navigation sûrs et efficaces sont planifiés (hors ligne) sur la base de la méthode du _[fast marching]{lang=en .en}_ (FMM). Dans le cadre de la méthode de planification de la navigation proposée, différentes contraintes et objectifs peuvent être pris en compte pour obtenir un chemin de référence véritablement réalisable. Deuxièmement, des stratégies de commande guidant les microrobots magnétiques le long du chemin de référence jusqu'à l'emplacement ciblé sont synthétisées. Pour ce faire, des lois de commande prédictives et optimales ont été mises en œuvre. Tous les modèles et stratégies de navigation proposés ont été évalués à travers diverses expérimentations dans différentes conditions sur les plateformes développées au Laboratoire PRISME

    Les innovations en microrobotique pour le biomédical

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    Stratégies de commande référencées multi-capteurs et gestion de la perte du signal visuel pour la navigation d'un robot mobile

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    The literature provides many techniques to design efficient control laws to realize robotic navigation tasks. In recent years, the sensors improvement gave rise to the sensor-based control which allows to define the robotic task in the sensor space rather than in the configuration space. In this context, as cameras provide high-rate meaningful data, visual servoing has been particularly investigated, and can be used to perform various and accurate navigation tasks. This method, which relies on the interaction between the camera and the visual features motions, consists in regulating an error in the image plane. Nonetheless, vision-based navigation tasks in cluttered environment cannot be expressed as a sole regulation of visual data. Indeed, in this case, it is necessary to preserve not only the robot safety (i.e. non-collision) but also the visual features visibility. This thesis addresses this issue and aims at developing sensor-based control laws allowing a mobile robot to perform vision-based tasks amidst possibly occluding obstacles. We have first proposed techniques able to fulfill simultaneously the two previously mentioned objectives. However, avoiding both collisions and occlusions often over-strained the robotic navigation task, reducing the range of realizable missions. This is the reason why we have developed a second approach which lets the visual features loss occurs if it is necessary for the task realization. Using the link between vision and motion, we have proposed different methods (analytical and numerical) to compute the visual signal as soon it becomes unavailable. We have then applied them to perform vision-based tasks in cluttered environments, before highlighting their interest to deal with a camera failure during the mission.La synthèse de lois de commande efficaces apparaît comme un enjeu important dans la réalisation autonome de tâches de navigation robotiques. Ce problème peut être abordé par différentes approches. L'une d'entre elles, la commande référencée capteur, permet de définir les boucles de commande directement à partir des mesures sensorielles au lieu de les exprimer en fonction de l'état du robot. Dans ce contexte, du fait de la richesse du signal vidéo, la vision apparaît comme un capteur privilégié pour la réalisation de tâches très variées de manière précise. Cependant, la commande référencée vision reposant sur la seule régulation des indices visuels dans l'image s'avère mal adaptée pour réaliser des tâches de navigation complexes dans des environnements encombrés d'obstacles. En effet, dans ce cas, il est nécessaire de garantir d'une part la sécurité du robot, et d'autre part la disponibilité permanente des indices visuels dans l'image. Ce sont précisément ces problèmes que nous avons voulu étudier dans le cadre de cette thèse. Notre contribution a consisté à définir des stratégies de commande référencées multi-capteurs pour un robot mobile réalisant une tâche référencée vision dans un environnement encombré d'obstacles susceptibles d'occulter le motif visuel. Nous avons tout d'abord proposé des lois de commandes permettant d'éviter à la fois les occultations et les collisions. Toutefois, les résultats obtenus ont montré que chercher à éviter simultanément ces deux phénomènes surcontraignait le mouvement du robot, limitant la gamme des missions réalisables. Nous avons alors développé une seconde approche consistant à tolérer temporairement la perte du signal visuel. Celle-ci repose sur l'exploitation de la réversibilité du lien vision/mouvement exprimé par le torseur d'interaction. Nous avons ainsi proposé dans un cadre général plusieurs méthodes (analytiques et numériques) de reconstruction du signal visuel lorsqu'il devient indisponible. Nous avons ensuite validé ch acune de ces méthodes dans le cas de la réalisation d'une tâche de navigation référencée vision dans un milieu encombré d'obstacles. Nous avons également montré l'intérêt de nos approches lorsque la caméra présente un défaut de fonctionnement pendant l'exécution d'une mission

    2D Robust Magnetic Resonance Navigation of a Ferromagnetic Microrobot using Pareto Optimality

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    International audienceThis paper introduces a two-dimensional autonomous navigation strategy of a 750 µm steel microrobot along a complex fluidic vascular network inside the bore of a clinical 3.0 T magnetic resonance imaging (MRI) scanner. To ensure successful magnetic resonance navigation (MRN) of a micro-robot along consecutive channels, the design of autonoumous navigation strategy is needed taking into account the major MRI technological constraints and physiological perturbations, e.g. non-negligible pulsatile flow, limitations on the magnetic gradient amplitude, MRI overheating, susceptibility artifacts uncertainties , and so on. An optimal navigation planning framework based on Pareto optimality is proposed in order to deal with this multiple-objective problem. Based on these optimal conditions, a dedicated control architecture has been implemented in an interventional medical platform for real-time propulsion, control and imaging experiments. The reported experiments suggest that the likelihood of controlling autonomously untethered 750 µm magnetic microrobots is rendered possible in a complex two-dimensional centimeter-sized vascular phantom. The magnetic microrobot traveled intricate paths at a mean velocity of about 4 mm s −1 with average tracking errors below 800 µm with limited magnetic gradients ±15 mT m −1 compatible with clinical MRI scanners. The experiments demonstrate that it is effectively possible to autonomously guide a magnetic microrobot using a conventional MRI scanner with only a software upgrade

    Modeling and Estimation of Self-Phoretic Magnetic Janus Microrobot With Uncontrollable Inputs

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