HAL-INSA Toulouse
Not a member yet
34325 research outputs found
Sort by
Very High Frequency Interpolation for Direct Torque Control
No full textInternational audienceTorque control enables agile and robust robot motion, but deployment is often hindered by instability and hardware limits. Here, we present a novel solution to execute whole-body linear feedback at up to 40 kHz on open-source hardware. We use this to interpolate non-linear schemes during real-world execution, such as inverse dynamics and learned torque policies. Our results show that by stabilizing torque controllers, high-frequency linear feedback could be an effective route towards unlocking the potential of torque-controlled robotics
Mie resonant silicon particles via bottom-up synthetic routes and assembled into 2d metasurfaces
No full textInternational audienceMie resonant silicon particles have strong scattering and thus are highly desirable building-blocks in metamaterials and metasurfaces. Most silicon resonators are produced via top-down fabrication methods.We presenttwo bottom-up syntheses followed by particle self-assembly, producing a silicon-based metasurface having a degree of disorder, and yet a high quality factor
Merging bioelectrochemical transducer and antenna functions for continuous monitoring in biological tissues: an innovative volume-saving strategy
No full textInternational audienceThe continuous monitoring of physiological parameters can provide crucial information to better understand and treat health disorders more efficiently. However, because the size of implantable sensors remains generally too large, numerous parts of the body can still not be accessed. We propose here to combine in a synergistic way the two most volumetric functions of a typical sensing device, i.e. the energy supply and the communication unit, to reduce the overall device footprint. The electrode of a biofuel cell (BFC), whose role is to deliver DC current, is merged with the antenna electrode, whose function is to provide radiofrequency alternating current, transforming de facto the BFC electrode into an antenna. This first proof-of-concept BFC, acting at the same time as an energy source and an antenna, enables wireless communication of glucose concentration over macroscopic distances. A novel dielectric screening strategy is also proposed as a trade-off between the analyte diffusion (BFC function), and electric field preservation (wireless communication function) to optimize the overall efficiency. Finally, we demonstrate that the integrity of the proposed device can be maintained after subcutaneous implantation in rats. These results pave the way for wireless miniaturized implantable devices for continuous monitoring in biological tissues.</div
Towards a CuSEF (CubeSat Systems Engineering Framework)
No full textCubeSat technology has lowered the barrier to entry into space, enabling small organizations and universities to rapidly design and launch miniature satellites. This trend has also created a market in which companies are jostling to sell these systems and the services they provide.Cubesats projects are very often carried out in very specific contexts with small teams and limited budgets. What's more, in the face of stiff competition, industry players are trying to compress development time to keep costs down and deliver the product as quickly as possible. This leads to a very high mission failure rate.A key factor of this high failure rate is the lack of a rigorous yet lightweight systems engineering process adapted to these small, fast-paced projects. Traditional standards for systems engineering (such as the ISO/IEC/IEEE 15288 lifecycle standard or space agency process standards like ECSS) are often not applied on CubeSat projects, as they can be overly complex, resource-intensive, or ill-suited to the constraints of CubeSat-class missions. NewSpace teams (small start-ups or academic groups with limited budgets and personnel) typically operate in a “garage development” style – ad hoc design-build efforts using off-the-shelf parts – which can result in missed engineering steps and inadequate testing.This paper introduces the CubeSat Systems Engineering Framework (CuSEF), tailored for NewSpace, that bridges the gap between heavyweight standards and the practical realities of CubeSat development. CuSEF combines a simplified process model with modern methods and tools to provide structure without undue burden. By adapting the ISO 29110 standard for very small entities and integrating essential requirements from the ECSS space engineering guidelines, the framework aims to enhance the reliability of CubeSat missions while optimizing development cost and time. The following sections review the state of the art, detail the CuSEF framework (its process, methods, and toolset), discuss expected benefits, and conclude with future perspectives
Solution synthesis of antiferromagnetic manganese nanoparticles
No full textInternational audienceNanoparticles have been frequently found to be more reactive than complexes made of the same metals and ligands. However, despite the considerable development of low-valent manganese complexes due to their relevance in catalysis, the chemistry of manganese metal nanoparticles remains severely underdeveloped. Using an organometallic approach, we describe the synthesis of Mn(0) nanoparticles. Thorough magnetic characterization evidences the antiferromagnetic behavior of non-oxidized nanoparticles. They feature highly electrophilic properties, which are highlighted by their catalytic properties in alkene hydrogenation and their irreversible reactions with oxygen-containing molecules. This result paves the way for the preparation of a new generation of manganese-based nanoparticles, which has so far been impossible due to the absence of a synthesis route
Sketchpose: Learning to Segment Cells with Partial Annotations
No full textInternational audienceThe most popular networks used for cell segmentation (e.g. Cellpose, Stardist, HoverNet,...) rely on a prediction of a distance map. It yields unprecedented accuracy but hinges on fully annotated datasets. This is a serious limitation to generate training sets and perform transfer learning. In this paper, we propose a method that still relies on the distance map and handles partially annotated objects. We evaluate the performance of the proposed approach in the contexts of frugal learning, transfer learning and regular learning on regular databases. Our experiments show that it can lead to substantial savings in time and resources without sacrificing segmentation quality. The proposed algorithm is embedded in a user-friendly Napari plugin
Modulation systématique de la charge et du spin de nanorubans de graphène sur MgO
No full textInternational audienceAbstract In order to take full advantage of graphene nanostructures in quantum technologies, their charge and spin state must be precisely controlled. Graphene quantum dots require external gating potentials to tune their ground state. Here, we show systematic manipulation of the electron occupation in graphene nanoribbons lying on MgO layers grown on Ag(001). Owing to the efficient electronic decoupling character of MgO, and the electropositive nature of the substrate, the ribbons host an integer number of electrons that depend on their length and shape. This results in the alternation between a non-magnetic closed-shell state and an open-shell paramagnetic system for even and odd electron occupations respectively. For the odd case, we find a narrow Coulomb correlation gap, which is the smoking gun of its spin-½ state. Comparisons of scanning tunnelling microscopy data with mean-field Hubbard simulations confirm the discretization of the ribbons’ electronic states and charge excess of up to 19 electrons per ribbon
Planification des activités d'une flotte de robots mobiles autonomes pour la logistique interne de systèmes de production
No full textNational audienc
Structure-Exploiting Sequential Quadratic Programming for Model-Predictive Control
No full textInternational audienceThe promise of model-predictive control in robotics has led to extensive development of efficient numerical optimal control solvers in line with differential dynamic programming because it exploits the sparsity induced by time. In this work, we argue that this effervescence has hidden the fact that sparsity can be equally exploited by standard nonlinear optimization. In particular, we show how a tailored implementation of sequential quadratic programming achieves state-of-the-art model-predictive control. Then, we clarify the connections between popular algorithms from the robotics community and well-established optimization techniques. Further, the sequential quadratic program formulation naturally encompasses the constrained case, a notoriously difficult problem in the robotics community. Specifically, we show that it only requires a sparsity-exploiting implementation of a state-of-the-art quadratic programming solver. We illustrate the validity of this approach in a comparative study and experiments on a torque-controlled manipulator. To the best of our knowledge, this is the first demonstration of closed loop nonlinear model-predictive control with constraints on a real robot
A Hamilton-Jacobi approach for the evolutionary dynamics of a model with gene transfer: characterizing monomorphic dynamics for non-concave fitness functions
No full textWe study the asymptotic behavior of an integro-dierential equation describing the evolutionary adaptation of a population structured by a phenotypic trait. The model takes into account mutation, selection, horizontal gene transfer and competition. Previous works, based on the numerical studies or theoretical study of the corresponding stationary problem, have shown that the dynamics of the solutions are rich and we may expect several qualitative outcomes. In this article, we characterize the dynamics of the solution in two regimes: 1) a situation where the solution concentrates around a dominant trait, evolving gradually to a trait determined by a balance between selection and horizontal gene transfer; 2) a situation where the solution concentrates around a dominant trait which evolves gradually to a maladapted trait such that the population becomes extinct (a situation known as the evolutionary suicide). Our analysis is based on an approach involving Hamilton-Jacobi equations with constraint. Previously, the solutions to such equations were characterized for globally concave growth rates. Here, we extend this approach to situations where the growth rate is not globally concave