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On-the-Fly Interrogation of Mobile Passive Sensors from the Fusion of Optical and Radar Data
No full textInternational audienceIn this paper a new method based on the fusion of optical and radar data is proposed to detect and remotely interrogate mobile and passive sensors. The sensors are detected in real time by using an optical camera, while their remote reading is carried out on the fly using a Frequency-Modulated Continuous-Wave radar. The proof-of-concept is established from the interrogation of a microfluidic temperature sensor placed on a conveyer belt
Efficient and Validated Numerical Evaluation of Abelian Integrals
No full textInternational audienceAbelian integrals play a key role in the infinitesimal version of Hilbert's 16th problem. Being able to evaluate such integrals - with guaranteed error bounds - is a fundamental step in computer-aided proofs aimed at this problem. Using interpolation by trigonometric polynomials and quasi-Newton-Kantorovitch validation, we develop a validated numerics method for computing Abelian integrals in a quasi-linear number of arithmetic operations. Our approach is both effective, as exemplified on two practical perturbed integrable systems, and amenable to an implementation in a formal proof assistant, which is key to provide fully reliable computer-aided proofs
Event-triggered boundary control of an unstable reaction diffusion PDE with input delay
No full textInternational audienceIn chemical, biological, or population (epidemiological) processes the feedback action may be considerably delayed by time-consuming chemical measurements or biological tests. With such large delays on the control action in mind, and motivated by the fact that in some of these systems only piecewise-constant inputs can be applied between time instants at which measurements trigger changes in control, we consider the problem of event-triggered stabilization of 1-D reaction-diffusion PDE systems with input delay. The approach relies on reformulating the delay problem as an actuated transport PDE which cascades into the reaction-diffusion PDE, and on the emulation of backstepping control. The paper proposes a static (state-dependent) triggering condition which establishes the time instants at which the control value needs to be updated. It is shown that under the proposed event-triggered boundary control, there exists a minimal dwelltime (independent of the initial conditions) between two triggering times which allows to guarantee the well-posedness of the closed-loop system, and the exponential stability. The stability analysis is based on Input-to-State stability theory for PDEs and small-gain arguments. A simulation example is presented to validate the theoretical results
Evidence of trapping and electrothermal effects in vertical junctionless nanowire transistors
No full textInternational audienceUnderstanding trap dynamics and formation of localized temperature hot-spots due to self-heating is crucial for the design optimization of emerging vertical junctionless nanowire transistors (VNWFET). This work investigates the operation of an 18 nm VNWFET technology, for the first time, leveraging pulsed current–voltage measurements. Results indicate increased trap activity as well as electrothermal effects with increasing pulse width. Multiphysics simulations are then used to provide a deeper insight into the nanoscale transport of the VNWFETs. We then incorporated these effects into the SPICE-compatible VNWFET compact model and further investigated the behaviors of trapping and electrothermal effects in basic logic circuits based on the compact model simulation
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms
No full textInternational audienceA major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation of algorithms that tackle social navigation remains hard because it involves not just robotic agents moving in static environments but also dynamic human agents and their perceptions of the appropriateness of robot behavior. In contrast, clear, repeatable, and accessible benchmarks have accelerated progress in fields like computer vision, natural language processing and traditional robot navigation by enabling researchers to fairly compare algorithms, revealing limitations of existing solutions and illuminating promising new directions. We believe the same approach can benefit social navigation. In this paper, we pave the road towards common, widely accessible, and repeatable benchmarking criteria to evaluate social robot navigation. Our contributions include (a) a definition of a socially navigating robot as one that respects the principles of safety, comfort, legibility, politeness, social competency, agent understanding, proactivity, and responsiveness to context, (b) guidelines for the use of metrics, development of scenarios, benchmarks, datasets, and simulators to evaluate social navigation, and (c) a design of a social navigation metrics framework to make it easier to compare results from different simulators, robots and datasets
Ground Reaction Forces and Moments Estimation from Embedded Insoles using Machine Learning Regression Models
No full textInternational audienceThe objective of this paper was to assess the possibility of estimating 6D ground reaction forces and moments during continuous double supports exercises using instrumented force insoles. Thanks to machine learning regression, the study evaluated the performance of an embedded solution in comparison to a reference laboratory grade force plate. While insoles were validated in the context of gait, few studies investigated their accuracy in estimating ground reaction forces and moments for rehabilitation exercises with both feet on the ground. Thus, popular ankle and hip strategies, squat and hula hoop exercises were investigated. The estimation accuracy was reported with a low average error of 1.6 ± 0.3% of the body weight and 1.2 ± 0.3% of the body weight times the body height along with a moderate correlation when using solely features extracted from insoles measurements. These results demonstrated the possibility of using embedded solutions to estimate the full ground reaction wrench if the learning process was applied for each specific task separately
Experimental Validation of Sensitivity-Aware Trajectory Planning for a Quadrotor UAV Under Parametric Uncertainty
No full textInternational audienceIn this work, we provide an experimental vali-dation of the recent concepts of closed-loop state and inputsensitivity in the context of robust flight control for a quadrotor(UAV) equipped with the popular PX4 controller. Our objectiveis to experimentally assess how the optimization of the referencetrajectory w.r.t. these sensitivity metrics can improve the closed-loop system performance against model uncertainties commonlyaffecting the quadrotor systems. To accomplish this, we presenta series of experiments designed to validate our optimizationapproach on two distinct trajectories, with the primary aimof assessing its precision in guiding the quadrotor through thecenter of a window at relatively high speeds. This approachprovides some interesting insights for increasing the closed-loop robustness of the robot state and inputs against physicalparametric uncertainties that may degrade the system’s perfor-mance
Lightweight Security for IoT Systems leveraging Moving Target Defense and Intrusion Detection
No full textInternational audienceAs more and more devices have communication capabilities, our world is becoming increasingly interconnected. This paradigm is called the Internet of Things (IoT). Most IoT devices have limitations in memory, computing capacity, and energy, thus making impossible to integrate fully-fledged secured solutions into them. Intrusion Detection Systems (IDS) and Moving Target Defense (MTD) are two acknowledged cyber defense techniques that have attracted researchers' attention but need to fit within the constraints of IoT systems. In this paper, based on our previous MTD work, we propose an in-node MTD strategy exhibiting hybrid (i.e., event- and time-based) movement. We specifically explore the MTD interaction with a lightweight detection mechanism to provide reactive defense on top of the by-design proactive-time-based MTD. We implemented and evaluated our proposal in a real IoT platform exposed to a Reduction-of-Quality (RoQ) attack by measuring the round-trip time and packet-loss rate of the system in four scenarios. Notably, we compared our proposal against a time-based-only MTD alternative, which demonstrates the promising results of our hybrid strategy
Shadow-mask evaporation for the fabrication of optical filters with spatially tailored thickness
No full textInternational audienceThe fabrication of optical filters whose reflection/transmission response is spatially-graded has been the object ofnumerous research studies over the past decades given their applications in areas including multi- and hyperspectralimaging, structural colouring and even holographic encryption. In this context, the key enabling feature is the ability totailor the thickness profile of at least one layer of the optical coating multilayer stack. To-date, this 3-dimensionalstructuration has been achieved either at the deposition stage or as an additional post-deposition process step. In theformer case, the technique relies on the shaping of the material deposition flux thanks to the insertion of a (moving)mask inside the evaporation or sputtering machine. As such, the method is usually limited to the implementation ofcentimetre-scale variations. A contrario, to reach sub-millimeter-scale features, the preferred approach is based on postdepositionlayer structuration, which is performed using grayscale lithography in the form of multi-(mask-)level opticallithography, or using e-beam or laser lithography. All these approaches are nevertheless relatively complex since theyinvolve either multiple steps or need a very precise calibration of the exposition curve.In this paper, we report that the evaporation through re-usable shadow masks can be used to create optical filterswhose spatial variations can be controlled with a ~70-μm-resolution. Using metal-mirror Fabry-Pérot interferometerstructures as representative optical filters, we demonstrate the ability to adjust the resonance wavelength, the filterbandwidth and extinction ratio, and the coupling strength and splitting in cascaded resonators
Lower Limbs Human Motion Estimation From Sparse Multi-Modal Measurements
No full textInternational audienceThis study aimed at the estimation of the 3D lower-limb joint kinematics during a sit-to-stand and a squat exercises using a new affordable motion capture system. Utilizing a reduced number of affordable visual inertial measurement units and markerless data, the study investigates the performance of these modalities in comparison to a reference stereophotogrammetric system. Indeed, markerless data are easily accessible from an RGB image, but few studies investigated their accuracy to perform inverse kinematics for rehabilitation exercise. Thus, ankle, knee, and hip joint center positions and joint angles were obtained through a novel sliding windows inverse kinematics algorithm. Joint angles were estimated with an average error of 8.1deg when inertial and visual data were used and 13.4deg when using solely markerless data. Joint center positions also displayed an estimation error reduced by 2.5 times when using the proposed approach over purely markerless data. These results, associated with the real affordability and ease of use of the proposed system open the door to future field applications in both rehabilitation and sport