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Visual Assistance in VR-based Robot Control: Towards a Reproducible Evaluation Scenario
No full textNational audienceImmersive technologies enhance industrial applications by creating virtual representations of manufacturing environments and providing visual assistance for tasks. Most studies in the literature are based on ad hoc scenarios, making comparison across studies challenging. In this research, 99 participants controlled a remote industrial robot using a VR headset in a reproducible maintenance task. They performed the task under three conditions: without assistance (control), text-based assistance, or attentional cueing (highlighting objects). We manipulated task difficulty (easy versus difficult) and assessed performance based on completion time and failure rate. Results showed visual assistance significantly shortened task completion time, with findings discussed
Modeling of the N 2 + ion in cold helium plasma: III. Relaxation of rotational excitations in N 2 +
No full textInternational audienceReaction rate constants of rotational transitions in the N 2 + ion ( j → j ′ , j ⩽ 36 ) induced by collisions with helium atoms have been calculated using recently reported cross-sections (Paláček 2024 Chem. Phys. Chem. 25 e202300469) obtained via classical trajectories run on the ground-state potential energy surface of the N 2 + /He collision complex obtained at a MCSCF/aug-cc-pVQZ level. Weak to medium electric fields ( E / N = 1 − 100 Td) have been considered. In addition, the role of vibrational excitations in N 2 + ( v = 0 → v ′ = 1 ) is also briefly discussed and shown negligible under the conditions considered. The calculated rate constants have been used to model the relaxation dynamics of rotationally excited N 2 + ions and to estimate its characteristic time scales as well as effective temperatures of relaxed N 2 + ions
Amplification of numerical wave packets for transport equations with two boundaries
No full textThe purpose of this note is to investigate the coupling of Dirichlet and Neumann numerical boundary conditions for the transport equation set on an interval. When one starts with a stable finite difference scheme on the lattice and each numerical boundary condition is taken separately with the Neumann extrapolation condition at the outflow boundary, the corresponding numerical semigroup on a half-line is known to be bounded. It is also known that the coupling of such numerical boundary conditions on a compact interval yields a stable approximation, even though large time exponentially growing modes may occur. We review the different stability estimates associated with these numerical boundary conditions and give explicit examples of such exponential growth phenomena for finite difference schemes with "small" stencils. This provides numerical evidence for the optimality of some stability estimates on the interval
Hoeffding decomposition of functions of random dependent variables
No full textInternational audienceHoeffding's functional decomposition is the cornerstone of many post-hoc interpretability methods. It entails decomposing arbitrary functions of mutually independent random variables as a sum of interactions. Many generalizations to dependent covariables have been proposed throughout the years, which rely on finding a set of suitable projectors. This paper characterizes such projectors under hierarchical orthogonality constraints and mild assumptions on the variable's probabilistic structure. Our approach is deeply rooted in Hilbert space theory, giving intuitive insights on defining, identifying, and separating interactions from the effects due to the variables' dependence structure. This new decomposition is then leveraged to define a new functional analysis of variance. Toy cases of functions of bivariate Bernoulli and Gaussian random variables are studied
Approximating the Shapley value with sampling : survey and new stratification techniques
No full textIn game theory, a cooperative game can be used to model a system able to provide a service to a set of users for a certain cost. An important topic related to cooperative games is the cost sharing which distributes the total cost of the system among the players. Shapley proposed in 1953 a cost-sharing mechanism nowadays known as the Shapley value. It is usually interpreted as assigning to each player the cost this player induces on the system. This cost assignment has many desirable properties but it is very time consuming to compute exactly when the number of users is large. Thus, a large effort has been directed towards its approximation. Many general purpose algorithms for computing the Shapley value use sampling, and in particular stratified sampling, in order to obtain a good approximation. In this paper, we provide a comprehensive overview for approximating the Shapley value with sampling with a focus on how and why stratified sampling helps enhancing the precision of the approximation. We also propose a new paradigm to apply stratification which is more flexible than the currently used schemes and allows one to adjust the stratification decisions to the result of the sampling process. We suggest a methodology to create datasets containing a large number of random games to test Shapley approximation algorithms. Finally, we report an extensive experimental study of all the algorithms described in the paper on the datasets created using the previous methodology
Représentations dérivées des variétés de caractères quantiques
No full textQuantum moduli algebras were introduced by Alekseev-Grosse-Schomerus and Buffenoir-Roche in the context of quantization of character varieties of surfaces and exist for any quasitriangular Hopf algebra . In this paper we construct representations of on cohomology spaces for all , where is any -module and is any -module endowed with a compatible -module structure. As a corollary and under suitable assumptions on , we obtain projective representations of mapping class groups of surfaces on such Ext spaces. This recovers the projective representations constructed by Lentner-Mierach-Schweigert-Sommerhäuser from Lyubashenko theory, when the category is used in their construction. Other topological applications are matrix-valued invariants of knots in thickened surfaces and representations of skein algebras on Ext spaces
Digital twins for military aircraft: A machine learning approach for monitoring structural aging
No full textInternational audienceUnlike civil aviation, where regular maintenance schedules are feasible, military aircraft are subjected to highly variable flight conditions based on mission requirements. This makes real- time assessment of structural fatigue critical for safety. Traditional approaches rely on physics-based models to predict mechanical strains, fatigue, and aging from input flight control data. While these models provide significant insights, they may not fully capture the complexities of real-world conditions and can benefit from refinement. Our research seeks to enhance these models by using machine learning to create digital twins of strain gauges for military aircraft, capable of predicting structural strains and aging based on input-output flight data.A part of these flight data, such as altitude, Mach number or others, are routinely measured during flight missions. In this work, structural strains are additionally recorded at critical points on one instrumented aircraft using strain gauges. The objective is then to develop a robust machine learning framework that simulates the behavior of critical aircraft strain gauges under varying operational conditions. In other words, using flight parameters as inputs, we aim to predict the strains experienced at specific points on the aircraft. This predictive capability can improve the planning of maintenance activities, guaranteeing maintenance in operational condition, and therefore enhancing flight safety.A key step in our project deals with the exploration of the high-dimensional flight data using autoencoders and other techniques, in order to capture complex relationships between flight parameters, reduce the dimensionality of the data, and group similar configurations together. This reduction is essential for improving the efficiency and accuracy of subsequent regression models, particularly in the context of semi-supervised learning, where we leverage both the reconstruction of input data and the prediction of structural strains to compensate for the lack of labeled data. In this context, we conduct a comparative analysis of various regression models, including tree-based algorithms, deep learning models, and semi-supervised approaches.Looking ahead, several key avenues are identified. One important perspective is the incorporation of physics-based insights into the machine learning framework, creating a hybrid model that leverages both data-driven predictions and physical laws. This integration would improve the model’s accuracy and its reliability. Additionally, the explainability of the data driven models, using techniques such as LIME (Local Interpretable Model-agnostic Explanations) or GEMS-AI, is crucial. By ensuring transparency in the predictions, we can provide users with the necessary insights to make informed decisions about aircraft maintenance
Optimization of surface texturing parameters in additively manufactured continuous fiber composites using abrasive waterjet technique for composite repair applications
No full textInternational audienc
Solving moment and polynomial optimization problems on Sobolev spaces
No full textUsing standard tools of harmonic analysis, we state and solve the problem of moments for non-negative measures supported on the unit ball of a Sobolev space of multivariate periodic trigonometric functions. We describe outer and inner semidefinite approximations of the cone of Sobolev moments. They are the basic components of an infinite-dimensional moment-sums of squares hierarchy, allowing to numerically solve non-convex polynomial optimization problems on infinite-dimensional Sobolev spaces with global convergence guarantee
