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A Modular Execution Architecture for Robust Multi-Robot Planning and Acting in Trans-Media Environments
No full textIn complex missions involving heterogeneous multi-robot teams, especially in transmedia systems that operate across environments such as air and water, robust execution frameworks must ensure both temporal coherence and resilience to uncertainty. These challenges stem from the need to manage dynamic mode transitions, closely linked inter-agent tasks, and execution-time failures. This paper introduces the Adaptive and Modular Architecture (AMA) Execution and Planning components. AMA-EXEC is a distributed execution framework designed to enable coherent, fault-tolerant mission execution in such conditions. AMA-EXEC uses the plans produced by AMA-PLAN, a PDDL-based planning framework. AMA-EXEC incorporates Simple Temporal Networks (STNs) to facilitate temporal reasoning; modular BTs to enable distributed execution; and runtime monitoring mechanisms to categorize failures, propagate delays, and execute partial replanning. In contrast to centralized, monolithic systems, AMA-EXEC organizes execution around collaborative robot teams and leverages real-time feedback to maintain synchronization and temporal alignment under disturbances. The framework's validation process involves the execution of simulated trans-media missions, encompassing concurrent tasks and a range of failure scenarios. The findings indicate enhanced execution continuity, extended complex cases application, and robust failure recovery in comparison to baseline methodologies. The AMA-EXEC system's modularity and generalizability render it suitable for a wide range of applications, including environmental monitoring, distributed exploration, and search-and-rescue operations
Étude de l'influence des phénomènes thermomécaniques générés par l'interaction faisceau laser matière sur la microstructure des revêtements élaborés par SLM : une approche multi-physique (Thèse sous embargo)
No full textThe aim of this study is to investigate the advection/convection mechanisms that occur during the additive manufacturing process on dissimilar materials. More specifically for this research, a group of materials which have distinct thermophysical characteristics, but which have the advantage of being perfectly miscible at high temperatures : - C35 (or XC38) steel is a material frequently used in manufacturing tools - Cobalt-Chromium-Molybdenum alloy for applications requiring high resistance to wear and high temperatures. The first part of this study focuses on the description of the stellite alloy, as it is barely characterized in terms of its thermal characteristics, especially at high temperatures. The multiphysics numerical models developed in the study provide access to a large amount of information on the behavior of the molten region as a function of the parameters of the FA L-PBF machine, with reference to a relatively small amount of initial data and a few basic assumptions. Multiphysics modeling is used to replicate the shape of the molten zone, visualize the flow of liquid metal and map the distribution of the various elements, taking into account the experimental results. To implement these manufacturing process models, we use the commercial simulation software COMSOL Multiphysics® . A series of models have been developed to simulate temperature variations, convective movements and chemical mixing. All these models enable us to predict the results of the various phenomena induced as a function of operating conditions.Cette étude vise à étudier les mécanismes d'advections/convections qui se produisent lors du processus de fabrication additive L-PBF sur des matériaux différents. Plus spécifiquement pour cette recherche, un ensemble de matériaux qui ont des caractéristiques thermophysiques distinctes, mais qui ont l'avantage d'être parfaitement miscibles à haute température : - l'acier C35 (ou XC38) qui est un matériau usuellement utilisé pour l'outillage- l'alliage stellite (composé de cobalt, de chrome et de molybdène) est un alliage adéquat pour les applications nécessitant de fortes caractéristiques en termes d'usure et de bonne tenue en température. Le premier aspect de cette étude se concentre sur la description de l'alliage de stellite, car il est très peu caractérisé en ce qui concerne ses caractéristiques thermiques, notamment à des températures élevées. Pour cela, des caractérisations sur les propriétés thermiques de la poudre ont été effectuées pour la capacité calorifique, la diffusivité thermique et la masse volumique de la poudre. En complément de ces mesures, une attention plus particulière sur les caractérisations thermo-optiques de la poudre et de l'alliage de stellite a été menée, notamment sur l'absorptivité et l'émissivité. L'utilisation des modèles numériques multiphysiques développés lors de cette étude permet d'accéder rapidement à une grande quantité d'informations sur le comportement de la zone fondue en fonction des paramètres de la machine FA L-PBF en se référant à un nombre de données de départ relativement restreint et à quelques hypothèses basiques. La modélisation multiphysique permet de reproduire la forme de la zone fondue, de visualiser les flux de métal liquide et de cartographier la répartition des différents éléments en tenant compte des résultats expérimentaux. Afin de mettre en œuvre ces modèles de procédé de fabrication, nous utilisons le logiciel de simulation commercial COMSOL Multiphysics. On a développé une série de modèles qui simulent les variations de température, les mouvements convectifs et le mélange des substances chimiques. Tous ces modèles permettent de prévoir les résultats des divers phénomènes induits en fonction des conditions opératoires
Interplay Between Intrinsically Disordered Proteins and Atomically Precise Gold Nanoclusters Modulates their Optical Properties
No full textInternational audienceUnderstanding how structural and optical properties of metallic nanoclusters can be tuned by proteins is crucial for the use of these hybrid molecules in biomedical applications. The interaction of proteins with ultrasmall, atomically-precise gold nanoclusters (Au-NCs) has been mainly investigated in the context of structured proteins, while their behavior with intrinsically disordered proteins (IDPs) remains unexplored. This work examines the structural and optical properties of Au-NCs interacting with bioengineered IDPs containing up to three cysteines. We show that, by exploiting the conformational flexibility of cysteine-containing IDPs, we can anchor proteins to Au-NCs in a position-specific manner, leading to new bioconjugates with properties that differ from those of the individual components. We observed an up to 15-fold photoluminescence enhancement depending on the number of cysteines anchored. By combining mass spectrometry, small-angle X-ray scattering (SAXS), and computational modelling, the ensemble structures of nine bioconjugates with different stoichiometries were elucidated, indicating their overall compactness. Our results suggest that the interface between these atomically-precise species and the conformationally fluctuating protein is responsible for the optical properties of these nanobioconjugates. This research improves our understanding of Au-NC– protein interactions, paving the way to novel nano-molecular hybrid conjugates with tunable properties for bioimaging and therapeutic applications
Charge transfer during sodium-ion intercalation in graphite-like anodes as determined by Raman spectroscopy
No full textInternational audienceSodium intercalation in graphite is known to be unstable, posing a challenge for energy storage applications based on this cation. This study combines Raman spectroscopy with first-principles calculations, including electron-phonon coupling, to investigate charge transfer mechanisms and stability in Na-intercalated graphite. Contrary to theoretical predictions on a pure Na graphite intercalated compound, Raman data show no evidence of so-called mechanical coupling between Na + ions and graphene layers. As we have selected a partially graphitized carbon with an intense 2D band for the anode, analyzing the Raman shifts of both the G and 2D bands is possible and allows us to discriminate between doping and lattice expansion treated as strain effects. The observed shifts are fully explained by a simple charge-transfer mechanism to each graphene layer. At stage one intercalation, a charge transfer value of -0.17±0.02 |e -| per carbon atom is determined. These findings highlight the ability of Raman spectroscopy to quantify charge transfer and differentiate intercalation behaviors between the various alkali metals.</div
Highly Accurate Expectation Values Using High-Order Relativistic Coupled Cluster Theory
No full textInternational audienceThis work presents the automatic generation of analytic first derivatives of the energy for general coupled-cluster models using the tenpi toolchain. We report the first implementation of expectation values for CCSDT and CCSDTQ methods within the DIRAC program package for relativistic molecular calculations. As pivotal calculations, we focus on the electric field gradient (EFG) evaluated at the lithium nucleus in LiX (X = H, F, Cl) compounds, enabling the extraction of the nuclear electric quadrupole moment Q(7Li), and at the aluminum nucleus in AlY (Y = H, F, Cl, Br) compounds, for the determination of Q(27Al). These high-order methods are applied to compute corrections for triple and quadruple excitations for the EFG, a crucial quantity for determining nuclear quadrupole moments. We obtain Q(27Al) = 0.146598 ± 0.000001 b, in excellent agreement with the recommended value, and Q(7Li) = −0.038624 ± 0.000292 b, which is smaller than the currently recommended value, and suggests the need for further investigation
On the optimal control of birhythmic oscillatory PWA systems: an application to the p53-Mdm2 network
No full textAccepted for publication in CDC 2025 - 64th IEEE Conference on Decision and Control, Dec 2025, Rio de Janeiro, BrazilIn this work, we tackle the problem of inducing optimal transfers between the two oscillatory regimes of a birhythmic genetic network, represented through a piecewise affine dynamical system. For that, we resort to an adaptation of Pontryagin's Maximum Principle to the hybrid setting, with a cost function that combines the transfer time and an L¹-control cost. We focus on a two-dimensional PWA model of the p53-Mdm2 network, a well-known tumor suppressor module that represents a key example of birhythmicity naturally found in mammalian cells. The resulting optimal control can be expressed in feedback form, and is able to remove an oscillatory mode of the system, allowing selection between low or high frequency oscillations of the bimodal genetic network
Two lectures on the enumeration of curves by means of floor diagrams
No full textWe discuss, following Mikhalkin, Brugallé, and others, the counting of curves on toric surfaces with prescribed genus, Newton polygon, and intersection pattern with the toric boundary divisor, both at assigned and unassigned points.The first lecture is dedicated to the proof of a correspondence theorem (for plane curves) with the counting of floor diagrams, using a degeneration of the projective plane to a chain of rational ruled surfaces. This is due to Brugallé and does not involve any tropical geometry.The second lecture explores the relations with tropical geometry. We discuss the correspondence theorem of Mikhalkin, and show how the corresponding tropical enumerative problem can be formulated in terms of the combinatorial problem of counting floor diagrams. We give many examples throughout, inspired by the study of the enumerative geometry of K3 surfaces, by degeneration to unions of surfaces with dual complex a tiling of the S 2 sphere.</div
Vers une maintenance prévisionnelle interprétable par modèles d’apprentissage automatique dans les systèmes complexes à composants tournants
No full textNational audiencePredictive maintenance has become essential in the context of Industry 4.0, particularly for critical rotating components within complex industrial systems, where failures can lead to significant costs and unplanned production downtimes. However, most predictive models currently used remain opaque and are often perceived as black boxes by operators, limiting their adoption in real-world settings. This thesis focuses on the development of interpretable and explainable approaches to predictive maintenance, aiming to combine predictive performance with transparency to enhance their acceptability in industrial environments. To achieve this objective, several contributions are proposed. First, a methodology for optimizing multivariate time windows is developed to improve the structuring of non-stationary time series used in predictive maintenance. This method enables the automatic determination of optimal segmentation parameters, thereby facilitating the extraction of relevant information for training predictive models. Next, Multiclass Neural Additive Models (MNAM) are introduced as explainable machine learning models tailored to multiclass classification problems encountered in industrial contexts, such as the prediction of the Remaining Useful Life (RUL) of rotating components, framed as a classification task. MNAMs preserve an inherently explainable structure, making the model’s decisions more understandable and trustworthy. Finally, a formal approach for simplifying complex predictive models is proposed, based on representing models as sets of rules. This methodology enables users to control the trade-off between predictive accuracy and interpretability, thus providing a clear and actionable understanding of the factors responsible for failures. These contributions were validated on two complex industrial systems at the Bosch plant in Rodez: GRIBS, dedicated to the machining of diesel injector components, and RETCO HPC, used for deep drilling of high-pressure connectors. The results demonstrate that the proposed approaches enable reliable RUL prediction while offering meaningful interpretations of the underlying degradation mechanisms. This thesis thus highlights the crucial importance of integrating explainability and interpretability into predictive maintenance methods, in direct response to the operational needs of modern industrial systems.La maintenance prévisionnelle est devenue essentielle dans l’industrie 4.0, notamment pour les composants tournants critiques des systèmes complexes industriels, dont la défaillance engendre des coûts importants et des arrêts de production non planifiés. Cependant, la majorité des modèles prédictifs utilisés restent opaques et sont souvent perçus comme des "boîtes noires" par les opérateurs, limitant ainsi leur adoption sur le terrain. Cette thèse se concentre sur le développement d’approches interprétables et explicables en maintenance prévisionnelle, combinant performance prédictive et transparence pour améliorer leur acceptabilité. Pour atteindre cet objectif, plusieurs contributions complémentaires sont proposées. Tout d’abord, une méthodologie d’optimisation des fenêtres temporelles multivariées est développée pour améliorer la structuration des séries temporelles non stationnaires utilisées dans la maintenance prévisionnelle. Cette méthode permet d’automatiser la détermination des paramètres optimaux de segmentation temporelle, facilitant ainsi l’extraction d’informations pertinentes pour l’entraînement des modèles prédictifs. Les Multiclass Neural Additive Models (MNAM) sont ensuite introduits comme des modèles d’apprentissage automatique explicables, adaptés aux problématiques de classification multiclasses rencontrées en milieu industriel, telles que la prédiction de la durée de vie restante (RUL) des composants tournants, formulée sous forme de classes. Les MNAM préservent une structure explicable par construction, facilitant l’interprétation des décisions prises par le modèle. Enfin, une approche formelle de simplification de modèles prédictifs complexes est proposée. Celle-ci repose sur la représentation d’un modèle sous forme de règles, avec une méthodologie permettant de contrôler le compromis entre performance prédictive et interprétabilité, afin d’offrir aux utilisateurs une compréhension claire et exploitable des facteurs responsables des défaillances. Ces contributions ont été validées sur deux systèmes industriels complexes de l’usine Bosch à Rodez : GRIBS, destiné à l’usinage de composants pour injecteurs diesel, et RETCO HPC, utilisé pour le perçage profond de connecteurs haute pression. Les résultats montrent que les approches proposées permettent de prédire le RUL tout en offrant une interprétation des mécanismes de dégradation observés. Cette thèse démontre ainsi l’intérêt majeur d’intégrer explicabilité et interprétabilité aux méthodes prédictives en maintenance prévisionnelle, répondant directement aux besoins opérationnels des systèmes industriels modernes
F4 and desmic quartic surfaces
No full textThe desmic pencil of quartic surfaces is part of a beautiful, but mostly forgotten chapter of the classical theory of algebraic surfaces: it is the only non-degenerate pencil of surfaces in P3 containing at least three completely reducible members. We observe in this note that it is closely related to the Weyl group of the root system F4, and can be recovered from a series of symmetric spaces deduced from the exceptional Lie algebras. We discuss the main properties of the pencil from this Lie theoretic point of view
Event triggered control and exponential stability for infinite dimensional linear systems
No full textInternational audienceThis article aims at providing a unified analysis of the exponential stabilization of some abstract infinite dimensional systems undergoing an event-triggering mechanism that samples the control input. The partial differential equation is supposed to be defined by a skew-adjoint operator and controlled and observed through bounded operators. The continuously controlled closed loop system is assumed to be exponentially stable and the goal is to prove that a well-designed event-triggering mechanism to rule the time updates of the sampled control will allow to keep such a stability property. The key of the proof relies on the existence of an adequate Lyapunov functional. Existence and regularity of the solution to the closed-loop event-triggered system are also proven, along with the avoidance of Zeno behavior