Search

International audience; In this paper, we propose a set-inversion approach to validate the controller of a nonlinear system that should satisfy some state constraints. We introduce the notion of follow set which corresponds to the set of all output vectors such that the desired dynamics can be followed without violating the state-constraints. This follow set can then be used to choose feasible trajectories that a mobile robot will be able to follow. An illustrative example with a robot towing a trailer is presented. This example is motivated by the safe control of a boat towing a marine magnetique sensor to find wrecks.

International audience; When implementing a non-continuous controller for a cyber-physical system, it may happen that the evolution function of the closed-loop system is not anymore piecewise continuous along the trajectory, mainly due to if statements inside the control algorithm. As a consequence, an unwanted chattering effect may occur. This behavior is often difficult to observe even in simulation. We propose here a set-membership method based on interval analysis to detect different types of discontinuities. One of them is the sliding surface where the state trajectory jumps indefinitely between two distinct behaviors. As an application, we consider the validation of a sailboat controller. We show that our approach is able to detect and explain some unwanted sliding effects that may be observed in rare and specific situations on our actual sailboat robots.

This paper presents a new approach to bounded-error state estimation involving time uncertainties. For a given bounded\ud observation of a continuous-time non-linear system, it is assumed that neither the values of the observed data nor their\ud acquisition instants are known exactly. For systems described by state-space equations, we prove theoretically and demonstrate\ud by simulations that the proposed constraint propagation approach enables the computation of bounding sets for the systems’\ud state vectors that are consistent with the uncertain measurements. The bounding property of the method is guaranteed even\ud if the system is strongly non-linear. Compared with other existing constraint propagation approaches, the originality of the\ud method stems from our definition and use of bounding tubes which enable to enclose the set of all feasible trajectories inside\ud sets. This method makes it possible to build specific operators for the propagation of time uncertainties through the whole\ud trajectory. The efficiency of the approach is illustrated on two examples: the dynamic localization of a mobile robot and the\ud correction of a drifting clock.

International audience; Localization for underwater robots remains a challenging issue. Typical sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply Simultaneous Localization and Mapping (SLAM) methods to perform localization. Reliable Robot Localization presents an innovative new method which can be characterized as a raw-data SLAM approach. It differs from extant methods by considering time as a standard variable to be estimated, thus raising new opportunities for state estimation, so far underexploited. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization. This book not only presents original contributions to the field of mobile robotics, it also offers new perspectives on constraint programming and set-membership approaches. It provides a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated throughout this book with realistic robotic applications.

National audience; Ces dernières décennies, la robotique mobile s’est développée largement dans des milieux structurés et déjà cartographiés. Dans desenvironnements inconnus et non-structurés, comme les planètes lointaines, les volcans, des grottes profondes, des zones irradiées, desveines karstiques, les bâtiments en feu, les fonds marins, la robotique change de nature.Non seulement, elle devient indispensable car l’humain peut difficilement intervenir de façon sécurisée, mais souvent l’opérateur ne peut plus aider les robots par téléopération. Ces derniers doivent alors posséder un maximum d’autonomie et d’intelligence afin de pouvoir accomplir leur mission. On parle alors de robotique exploratoire car le robot doit cartographier son environnement, prendre des décisions, se localiser et être capable de revenir.

International audience; Existing controllers for sailboat robots are usually developed for speed performances and for long straight lines. In this context, the accuracy is not the main concern. In this paper, we consider the tight slalom problem which requires accuracy. We propose a feedback-linearization based method combined with a vector field approach to control the sailboat. Some simulations show that the robot is able to perform the slalom without missing any gate.

International audience; In this paper, we describe a method based on interval arithmetic and contractors to compute an envelope containing the trajectory of a robot from usual proprioceptive and exteroceptive data, using a simple state equation model. To illustrate the applicability of the method, data from the euRathlon 2015, a multi-domain robotics competition, will be processed to build an estimation of the trajectory of a low-cost AUV (Autonomous Underwater Vehicle), navigating with the help of acoustic communication and ranging with an ASV (Autonomous Surface Vehicle).

This paper proposes a new method for guaranteed integration of state equations. Within this framework, the variables of interest are trajectories submitted to both arithmetic and differential equations. The approach consists in formalizing a problem thanks to a constraint network and then apply these constraints to sets of trajectories. The contribution of the paper is to provide a reliable framework to enclose the solutions of these differential equations. Its use is shown to be simple, more general and more competitive than existing approaches dealing with guaranteed integration, especially when applied to mobile robotics. The flexibility of the developed framework allows to deal with non-linear differential equations or even differential inclusions built from datasets, while considering observations of the states of interest. An illustration of this method is given over several examples with mobile robots. A contractor-based approach is proposed for guaranteed integration of state equations.The framework is based on the use of tubes as envelopes of feasible trajectories.A dedicated differential contractor is provided to deal with dynamical systems.The use of tubes is well suited for multi-differential and non-linear equations.An illustration of this approach is given over several mobile robotics examples.

International audience; The WRSC (World Robotic Sailing Championship) / IRSC (International Robotic Sailing Conference) is an international and annual competition and conference that aims at stimulating the development of autonomous marine robotics and its applications. The competition, originally designed for sailboats, is also opened to motorboats as a separate category since 2013. In this paper, we will present the competition through the example of the 2013 edition, and show its results, specificities, issues as well as improvements for the next editions

International audience; This paper proposes to transform a sailboat robot into a big wind turbine (or windmill) corresponding to the boat itself. The main idea is to make the sailboat rotating as fast as possible. When the wind open the sail, the mainsheet is able to pull a generator in order to produce electric energy. The resulting controller is simple to implement and its parameters are easy to tune. A simulated test-case shows that the proposed technique could generate an average power of approximatively 100W

International audience; Moving huge objects floating at the surface of the ocean (such as containersor icebergs) with boats requires many human operators and a lot of energy.This is mainly due to the fact that when humans operate such equipment, time iscostly. Now, when we have time (as when robots operate, for instance), it is possibleto move arbitrarily large objects, for over long distances, with a limited quantity ofenergy. This is a consequence of the fact that in the water, the friction forces areproportional to the square of the speed (i.e., when we go slowly, we have almostno friction). This paper proposes the use of a sailboat robot to tow large objects. Itshows which control law could be used is order to (i) avoid loops inside the towingcable, (ii) avoid collisions between the robot and the towed object, and (iii) movethe object toward the desired direction. The control law is validated on a simulationwhere the object to be towed has to follow a trajectory corresponding to a largecircle.

International audience; A sailboat is a strongly non-linear system that however has been proven to be easily controllable. Indeed, its mechanical design comes from an evolution from thousands of years with two main concerns: having a fast, reliable and ef cient vehicle while being easily controlled by humans. This article describes the functioning, the validation process and the performances of a simple controller, inspired from what navigators do, through tests made on the sailboat robot VAIMOS built by IFREMER for oceanography. This controller requires tweaking few parameters with real physical meaning while ensuring accurate trajectory following, needed to make oceanographic measurements in a speci c area.

International audience; Un robot voilier est un système fortement nonlinéaire qui pourtant se commande relativement facilement. En effet, sa conception mécanique découle d'une évolution pragmatique sur plusieurs milliers d'années avec pour double objectif : celui d'une machine rapide et celui d'avoir un véhicule facile à commander. Cet article propose une stratégie de régulation d'un robot voilier inspirée de celle utilisée par les navigateurs. Le régulateur qui en résulte est simple, avec peu de paramètres à régler et ayant un sens physique évident. Un test sur le robot voilier Vaimos est présenté afin d'illustrer les performances du régulateur.

WOS; International audience; This paper deals with offline nonlinear state estimation where measurements are available only when some given equality conditions are satisfied. For this type of problems, which are often met in robot localization when sonar or radar are involved, the data are qualified as fleeting because the measurements are available only at some given unknown dates. In this paper, the first approach able to deal with nonlinear estimation with fleeting data is presented. An illustration related to offline robot localization with a laser rangefinder will be given.

This thesis studies the simultaneous localization and mapping problem for submarine robots, and its resolution methods using interval analysis. The principle of SLAM (Simultaneous Localization And Mapping) is the following: a submarine robot usually knows its initial position (when it is at the surface thanks to a GPS), its moving model (approximately) and has sensors enabling it to estimate its position (pressure sensor to get its depth, DVL to get its speed and measure its distance to the sea floor, inertial navigation system to get its orientation) and see its surrounding environment (sonar). However, in spite of all these sensors, the more it moves, the more its position estimation errors increase: the robot is lost. By going next to the same objects (or any distinguishable mark in its environment) several times, it should be able to evaluate their position (with a given accuracy) the first time from its own position (cartography from localization), then compute and correct its trajectory evaluation by taking them as mark next time when it is lost (localization from cartography). Because measurements from sensors or variables used to describe the behaviour of robots are often erroneous, they can be represented using different ways: probabilistic distributions, particles, continuous sets... Sensors or actuators manufacturers usually provide bounds (related to precision, accuracy...). Therefore, we can represent these values as intervals. Set-membership methods such as interval analysis enable to obtain results from equations involving intervals. The main advantage of these methods is that it is sure that no solution is lost (taking into account the assumptions made), contrary to probabilistic approaches, where the most probable solutions are obtained. In this thesis, the use of intervals computations for the SLAM of underwater robots and a comparison between several existing methods are studied. Additionally, a new method to handle better the problem of fleeting data (data that are only significant during short and unknown time intervals), often met with data from sonars, will be proposed. Applications of this work are for example in the development of autonomous submarine robots (often called AUVs for Autonomous Underwater Vehicles or UUVs for Unmanned Underwater Vehicles). Indeed, contrary to teleoperated robots, they must be able to localize themselves in their environment to do their work. These robots can do several missions: hydrographic data collection, shipwrecks or objects (sea mines...) localization, surveillance (pollution detection, pipelines surveys...)... Nowadays, those tasks are mostly done by humans, directly with divers or indirectly using teleoperated submarines when the conditions are dangerous or difficult.; Cette thèse étudie le problème de la localisation et cartographie simultanées des robots sous-marins, et ses méthodes de résolution utilisant le calcul par intervalles. Le principe du SLAM (Simultaneous Localization And Mapping, ou cartographie et localisation simultanées) est le suivant: un robot sous-marin connait en général sa position initiale (lorsqu'il est à la surface grâce à un GPS), son modèle de déplacement (très approximativement) et possède quelques capteurs l'aidant à estimer sa position (capteur de pression pour mesurer sa profondeur, loch Doppler pour mesurer sa vitesse et sa distance au fond, centrale inertielle pour mesurer son orientation) et voir ce qui l'entoure (sonar). Pourtant, malgré tous ces capteurs, plus il avance, plus ses erreurs d'estimation de position s'accumulent: le robot se perd. En passant et repassant devant plusieurs objets (ou éléments remarquables quelconques de son environnement), il va pouvoir évaluer leur position (plus ou moins précisément) une première fois à partir de la sienne (cartographie grâce à sa localisation), puis recalculer sa trajectoire en les prenant comme repère les fois suivantes quand il est perdu (localisation grâce à sa cartographie). Les mesures de capteurs ou variables utilisées pour décrire les robots étant souvent entachées d'erreurs, elles peuvent être représentées de différentes façons: distributions probabilistes, nuages de points, ensembles continus... En général, les données constructeur des capteurs ou actionneurs du robot nous indiquent des bornes (liées à la précision...). On peut donc représenter ces valeurs sous forme d'intervalles. Les méthodes ensemblistes telles que l'analyse par intervalles permettent d'obtenir des résultats à partir d'équations sur des intervalles. L'avantage de ces méthodes est qu'on est sûr de ne perdre aucune solution (compte tenu des hypothèses faites), contrairement à celles utilisant l'approche probabiliste, où on n'obtient parfois que les solutions les plus probables. Dans cette thèse, l'utilisation du calcul par intervalles dans le cadre du SLAM appliqué aux robots sous-marins et une comparaison entre plusieurs méthodes existantes seront étudiées. De plus, une nouvelle méthode permettant de mieux gérer le problème des données fugaces (données seulement significatives à des instants bien précis et inconnus), rencontré notamment avec des données provenant de sonars, sera proposée. Les applications de ces travaux concernent par exemple le développement de robots sous-marins autonomes (souvent appelés AUVs pour Autonomous Underwater Vehicles ou UUVs pour Unmanned Underwater Vehicles). En effet, contrairement aux robots téléguidés par des humains, ceux-ci doivent eux-mêmes être capables de se repérer dans leur environnement pour effectuer leur travail. Ces robots peuvent avoir des missions variées: relevé de données hydrographiques, localisation d'épaves (bateau, avion...) ou objets dangereux (mines...), surveillance (détection de pollution, vérification de l'état de pipelines...)... Actuellement, ces tâches sont principalement réalisées par des humains, directement avec des plongeurs, ou indirectement avec des sous-marins téléopérés pour les travaux les plus dangereux ou difficiles d'accès.

International audience; In this paper we will apply interval methods to solve the problem of robust localization of an underwater robot. The localization problem is cast into a constraint satisfaction problem (CSP) where constraint propagation algorithms are particularly efficient. The method is designed to work in real environments with numerous outliers. Besides, we used a new approach to represent the map by a binary image. This allow us to represent even unstructured maps. We tested the algorithm on a real data set gathered by an underwater robot in a marina located in Costa Brava.

International audience; This paper provides a new submarine experiment and shows the results of an interval SLAM (Simultaneous Localization And Mapping) method. The SLAM problem is cast into a constraint satisfaction problem where interval propagation algorithms are particularly efficient. The resulting method is applied to the localization of a submarine robot from the GESMA (Groupe d'Etudes Sous-Marines de l'Atlantique), the Daurade during an experiment in the Douarnenez bay, in Brittany (France).

Dans cet article, nous allons montrer que le problème du lancé de rayon couramment utilisé en graphisme et un problème d'analyse en stabilité d'un système paramétrique linéaire invariant sont deux problèmes très semblables. Nous allons proposer un algorithme unique utilisant le calcul par intervalles capable de résoudre ces deux problèmes de façon garantie et efficace.

The localization of underwater robots remains a challenging issue. Usual sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply usual Simultaneous Localization and Mapping (SLAM) methods to perform a localization.Hence, innovative approaches have to be explored. The presented method can be characterized as a raw-data SLAM approach, but we propose a temporal resolution — which differs from usual methods — by considering time as a standard variable to be estimated. This concept raises new opportunities for state estimation, under-exploited so far. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization.This thesis is thus not only a contribution in the field of mobile robotics, it also offers new perspectives in the areas of constraint programming and set-membership approaches. We provide a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated along this work with realistic robotics applications.; Aujourd'hui, la localisation de robots sous-marins demeure une tâche complexe. L'utilisation de capteurs habituels est impossible sous la surface, tels que ceux reposant sur les systèmes de géolocalisation par satellites. Les approches inertielles sont quant à elles limitées par leur forte dérive dans le temps. De plus, les fonds marins sont généralement homogènes et non structurés, rendant difficile l'utilisation de méthodes SLAM connues, qui couplent la localisation et la cartographie de manière simultanée.Il devient donc nécessaire d'explorer de nouvelles alternatives. Notre approche consiste à traiter un problème de SLAM de manière purement temporelle. L'originalité de ce travail est de représenter le temps comme une variable classique qu'il faut estimer. Cette stratégie soulève de nouvelles opportunités dans le domaine de l'estimation d'état, permettant de traiter de nombreux problèmes sous un autre angle. Toutefois, une telle résolution temporelle demande un ensemble d'outils théoriques qu'il convient de développer.Cette thèse n'est donc pas seulement une contribution dans le monde de la robotique mobile, elle propose également une nouvelle démarche dans les domaines de la propagation de contraintes et des méthodes ensemblistes. Cette étude apporte de nouveaux outils de programmation par contracteurs qui permettent le développement de solveurs pour des systèmes dynamiques. Les composants étudiés sont mis en application tout au long de ce document autours de problèmes robotiques concrets.