Lie symmetries applied to guaranteed integration: application to mobile robotics localisation

[no abstract available

Aggressive Memory Speculation in HW/SW Co-Designed Machines

International audienceSingle-ISA heterogeneous systems (such as ARM big.LITTLE) are an attractive solution for embedded platforms as they expose performance/energy trade-offs directly to the operating system. Recent works have demonstrated the ability to increase their efficiency by using VLIW cores, supported through Dynamic Binary Translation (DBT) to maintain the illusion of a single-ISA system. However, VLIW cores cannot rival with Outof- Order (OoO) cores when it comes to performance, mainly because they do not use speculative execution. In this work, we study how it is possible to use memory dependency speculation during the DBT process. Our approach enables fine-grained speculation optimizations thanks to a combination of hardware and software. Our results show that our approach leads to a geo-mean speed-up of 10% at the price of a 7% area overhead

Reliable Non-Linear State Estimation Involving Time Uncertainties

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

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987

Localisation fiable de robots : une approche de programmation par contraintes sur des systèmes dynamiques

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

Brunovsky Decomposition for Dynamic Interval Localization

This paper proposes a new set-membership method for estimating the trajectories of dynamical systems, when the states are completely unknown and only non-linear observations are available. The first part of the proposed method is symbolic and follows the decomposition of Brunovsky, , it decomposes the set of differential equations describing the dynamical system into two blocks of constraints: one block gathers non-linear analytical equations that do not involve differential operators, while the other block is composed of linear chains of integrators. The second part of the method, that relies on the symbolic decomposition, is numerical and based on a contractor approach. It involves a specific optimal operator for narrowing the sets of feasible solutions. This approach is shown to be efficient on a difficult problem of dynamic localization of a mobile robot, without any prior knowledge about its states

Exact bounded-error continuous-time linear state estimator

International audienceThis paper proposes an interval-based method for estimating the state of a linear continuous-time dynamical system. In this work, we assume that the measurements are provided at discrete times and that all errors are bounded. Interval analysis is used to propagate the interval uncertainties continuously over time. The resulting method is guaranteed to never lose any feasible solution and provides an optimal polygonal enclosure of the state trajectory. A reproducible example illustrates the principle of the method

Hybrid-JIT : Compilateur JIT Matériel/Logiciel pour les Processeurs VLIW Embarqués

National audienceLa compilation JIT (Just-In-Time) est largement utilisée dans les systèmes embarqués actuels (principalement grâce à la machine virtuelle Java). Lorsque l'architecture ciblée est un proces-seur VLIW (Very Long Intruction Word), la compilation JIT devient plus complexe à cause de l'étape d'ordonnancement des instructions et d'allocation des registres, réduisant ainsi ses bé-néfices. Dans ce travail, nous présentons un compilateur JIT hybride dans lequel la gestion du JIT est réalisée de manière logicielle tandis qu'un accélérateur matériel est utilisé pour les phases plus coûteuses telles que l'ordonnancement des instructions. Une étude expérimentale montre que cette approche mène à une compilation jusqu'à 15 fois plus rapide et 18 fois moins coûteuse en énergie par rapport à une approche purement logicielle

Hybrid-DBT: Hardware/Software Dynamic Binary Translation Targeting VLIW

International audienceIn order to provide dynamic adaptation of the performance/energy trade-off, systems today rely on heterogeneous multi-core architectures (different micro-architectures on a chip). These systems are limited to single-ISA approaches to enable transparent migration between the different cores. To offer more trade-off, we can integrate statically scheduled micro-architecture and use Dynamic Binary Translation (DBT) for task migration. However, in a system where performance and energy consumption are a prime concern, the translation overhead has to be kept as low as possible.In this paper we present Hybrid-DBT, an open-source, hardware accelerated DBT system targeting VLIW cores. Three different hardware accelerators have been designed to speed-up critical steps of the translation process. Experimental study shows that the accelerated steps are two orders of magnitude faster than their software equivalent. The impact on the total execution time of applications and the quality of generated binaries are also measured

Lie symmetries applied to interval integration

International audienceIn this paper, we propose a new approach for improving significantly existing guaranteed integration methods for state equations with uncertain initial conditions. We first find a tube that encloses the solution of the differential equation assuming that the initial state is known. Then, using Lie symmetries, we inflate the tube in order to contain the uncertainty associated with the initial state. The method is shown to be efficient on examples coming from reachability analysis and robotics