"A number of outstanding problems in robotic motion and manipulation involve tasks where degrees of freedom (DoF), be they part of the robot, an object being manipulated, or the surrounding environment, cannot be accurately controlled by the actuators of the robot alone. Rather, they are also controlled by physical properties or interactions - contact, robot dynamics, actuator behavior - that are influenced by the actuators of the robot. In particular, we focus on two important areas of poorly controlled robotic manipulation: motion planning for deformable objects and in deformable environments; and manipulation with uncertainty. Many everyday tasks we wish robots to perform, such as cooking and cleaning, require the robot to manipulate deformable objects. The limitations of real robotic actuators and sensors result in uncertainty that we must address to reliably perform fine manipulation. Notably, both areas share a common principle: contact, which is usually prohibited in motion planners, is not only sometimes unavoidable, but often necessary to accurately complete the task at hand. We make four contributions that enable robot manipulation in these poorly controlled tasks: First, an efficient discretized representation of elastic deformable objects and cost function that assess a ``cost of deformation' for a specific configuration of a deformable object that enables deformable object manipulation tasks to be performed without physical simulation. Second, a method using active learning and inverse-optimal control to build these discretized representations from expert demonstrations. Third, a motion planner and policy-based execution approach to manipulation with uncertainty which incorporates contact with the environment and compliance of the robot to generate motion policies which are then adapted during execution to reflect actual robot behavior. Fourth, work towards the development of an efficient path quality metric for paths executed with actuation uncertainty that can be used inside a motion planner or trajectory optimizer."

Identity based cryptography was first proposed by Shamir in 1984. Rather than deriving a public key from private information, which would be the case in traditional public key encryption schemes, in identity based schemes a user's identity plays the role of the public key. This reduces the amount of computations required for authentication, and simplifies key-management. Efficient and strong implementations of identity based schemes are based around easily computable bilinear mappings of two points on an elliptic curve onto a multiplicative subgroup of a field, also called pairing. The idea of utilizing the identity of the user simplifies the public key infrastructure. However, since pairing computations are expensive for both area and timing, the proposed identity based cryptosystem are hard to implement. In order to be able to efficiently utilize the idea of identity based cryptography, there is a strong need for an efficient pairing implementations. Pairing computations could be realized in multiple fields. Since the main building block and the bottleneck of the algorithm is multiplication, we focused our research on building a fast and small arithmetic core that can work on multiple fields. This would allow a single piece of hardware to realize a wide spectrum of cryptographic algorithms, including pairings, with minimal amount of software coding. We present a novel unified core design which is extended to realize Montgomery multiplication in the fields GF(2^n), GF(3^m), and GF(p). Our unified design supports RSA and elliptic curve schemes, as well as identity based encryption which requires a pairing computation on an elliptic curve. The architecture is pipelined and is highly scalable. The unified core utilizes the redundant signed digit representation to reduce the critical path delay. While the carry-save representation used in classical unified architectures is only good for addition and multiplication operations, the redundant signed digit representation also facilitates efficient computation of comparison and subtraction operations besides addition and multiplication. Thus, there is no need for transformation between the redundant and non-redundant representations of field elements, which would be required in classical unified architectures to realize the subtraction and comparison operations. We also quantify the benefits of unified architectures in terms of area and critical path delay. We provide detailed implementation results. The metric shows that the new unified architecture provides an improvement over a hypothetical non-unified architecture of at least 24.88 % while the improvement over a classical unified architecture is at least 32.07 %. Until recently there has been no work covering the security of pairing based cryptographic hardware in the presence of side-channel attacks, despite their apparent suitability for identity-aware personal security devices, such as smart cards. We present a novel non-linear error coding framework which incorporates strong adversarial fault detection capabilities into identity based encryption schemes built using Tate pairing computations. The presented algorithms provide quantifiable resilience in a well defined strong attacker model. Given the emergence of fault attacks as a serious threat to pairing based cryptography, the proposed technique solves a key problem when incorporated into software and hardware implementations. In this dissertation, we also present an efficient accelerator for computing the Tate Pairing in characteristic 3, based on the Modified Duursma Lee algorithm.

Because of the increasingly demanding tasks that robotic systems are asked to perform, there is a need to make them more reliable, intelligent, versatile and self-sufficient. Furthermore, throughout the robotic system?s operation, changes in its internal and external environments arise, which can distort trajectory tracking, slow down its performance, decrease its capabilities, and even bring it to a total halt. Changes in robotic systems are inevitable. They have diverse characteristics, magnitudes and origins, from the all-familiar viscous friction to Coulomb/Sticktion friction, and from structural vibrations to air/underwater environmental change. This thesis presents an on-line environmental Change, Detection, Isolation and Accommodation (CDIA) scheme that provides a robotic system the capabilities to achieve demanding requirements and manage the ever-emerging changes. The CDIA scheme is structured around a priori known dynamic models of the robotic system and the changes (faults). In this approach, the system monitors its internal and external environments, detects any changes, identifies and learns them, and makes necessary corrections into its behavior in order to minimize or counteract their effects. A comprehensive study is presented that deals with every stage, aspect, and variation of the CDIA process. One of the novelties of the proposed approach is that the profile of the change may be either time or state-dependent. The contribution of the CDIA scheme is twofold as it provides robustness with respect to unmodeled dynamics and with respect to torque-dependent, state-dependent, structural and external environment changes. The effectiveness of the proposed approach is verified by the development of the CDIA scheme for a SCARA robot. Results of this extensive numerical study are included to verify the applicability of the proposed scheme.

Path following and lateral stability are crucial issues for autonomous vehicles. Moreover, these problems increase in complexity when handling heavy-duty vehicles due to their poor manoeuvrability, large sizes and mass variation. In addition, uncertainties on mass may have the potential to significantly decrease the performance of the system, even to the point of destabilising it. These parametric variations must be taken into account during the design of the controller. However, robust control techniques usually require offline adjustment of auxiliary tuning parameters, which is not practical and leads to sub-optimal operation. Hence, this work presents an approach to path-following and lateral control for autonomous heavy-duty vehicles subject to parametric uncertainties by using a robust recursive regulator. The main advantage of the proposed controller is that it does not depend on the offline adjustment of tuning parameters. Parametric uncertainties were assumed to be on the payload, and an H∞ controller was used for performance comparison in simulations. The performance of both controllers is evaluated in a double lane-change manoeuvre. Simulation results showed that the proposed method had better performance in terms of robustness, lateral stability, driving smoothness and safety, which demonstrates that it is a very promising control technique for practical applications. Ultimately, experiment tests in a rigid heavy-duty truck validate what was found in simulation results. / O seguimento de caminho e a estabilidade lateral são questões cruciais para veículos autônomos. Além disso, devido à baixa capacidade de manobra, tamanho e grande variação de massa, estes problemas se tornam mais complexos quando se trata de veículos pesados. Adicionalmente, as incertezas na massa têm o potencial de diminuir significativamente o desempenho do sistema, chegando ao ponto de desestabilizá-lo, assim, essas variações paramétricas devem ser consideradas durante o projeto do controlador. No entanto, as técnicas de controle robusto geralmente exigem o ajuste off-line de parâmetros auxiliares do controlador, o que não é prático e lava a uma operação sub-ótima. Assim, este trabalho apresenta uma abordagem de controle de seguimento de caminho e controle lateral para veículos pesados autônomos sujeitos a incertezas paramétricas usando um regulador robusto recursivo. A principal vantagem deste controlador é que ele não depende do ajuste off-line de parâmetros. Assumiu-se que as incertezas paramétricas estavam na carga do veículo, e um controlador H∞ foi usado para comparar o desempenho em simulação. O desempenho de ambos os controladores é avaliado em uma manobra de mudança de faixa. Os resultados de simulação mostraram que o método proposto apresentou melhor desempenho em termos de robustez, estabilidade lateral, suavidade na condução e segurança, o que o demonstra como uma técnica de controle bastante promissora para aplicações práticas. Por fim, testes experimentais em um caminhão rígido reforçam os resultados obtidos em simulação.

In this thesis, we present some contributions to the Markov jump linear systems theory in a context of partial information on the Markov chain. We consider that the state of the Markov chain cannot be measured, but instead there is only an observed variable that could model an asynchronous phenomenon between the application and the plant, or a simple fault detection and isolation device. In this formulation, we investigate the problem of designing controllers and filters depending only on the observed variable in the context of H2, H?, and mixed H2/H? control theory. Numerical examples and academic applications are presented for active-fault tolerant control systems and networked control systems. / Nesta tese, apresentamos algumas contribuições para a teoria de sistemas lineares com saltos markovianos em um contexto de observação parcial da cadeia de Markov. Consideramos que o estado da cadeia de Markov não pode ser medido, porém existe uma variável observada que pode modelar um fenômeno assíncrono entre a aplicação e a planta, ou ainda um dispositivo de detecção de falhas simples. Através desse modelo, investigamos o problema da síntese de controladores e filtros que dependem somente da variável observada no contexto das teorias de controle H2, H?, e misto H2/H?. Exemplos numéricos e aplicações acadêmicas são apresentadas no âmbito dos sistemas de controle tolerantes a falhas e dos sistemas de controle através da rede.

L'imagerie hyperspectrale (HSI) repose sur le fait que, pour un matériau donné, la quantité de rayonnement émis varie avec la longueur d'onde. Les capteurs HSI mesurent donc le rayonnement des matériaux au sein de chaque pixel pour un très grand nombre de bandes spectrales contiguës et fournissent des images contenant des informations à la fois spatiale et spectrale. Les méthodes classiques de détection adaptative supposent généralement que le fond est gaussien à vecteur moyenne nul ou connu. Cependant, quand le vecteur moyen est inconnu, comme c'est le cas pour l'image hyperspectrale, il doit être inclus dans le processus de détection. Nous proposons dans ce travail d'étendre les méthodes classiques de détection pour lesquelles la matrice de covariance et le vecteur de moyenne sont tous deux inconnus.Cependant, la distribution statistique multivariée des pixels de l'environnement peut s'éloigner de l'hypothèse gaussienne classiquement utilisée. La classe des distributions elliptiques a été déjà popularisée pour la caractérisation de fond pour l’HSI. Bien que ces modèles non gaussiens aient déjà été exploités dans la modélisation du fond et dans la conception de détecteurs, l'estimation des paramètres (matrice de covariance, vecteur moyenne) est encore généralement effectuée en utilisant des estimateurs conventionnels gaussiens. Dans ce contexte, nous analysons de méthodes d’estimation robuste plus appropriées à ces distributions non-gaussiennes : les M-estimateurs. Ces méthodes de détection couplées à ces nouveaux estimateurs permettent d'une part, d'améliorer les performances de détection dans un environment non-gaussien mais d'autre part de garder les mêmes performances que celles des détecteurs conventionnels dans un environnement gaussien. Elles fournissent ainsi un cadre unifié pour la détection de cibles et la détection d'anomalies pour la HSI. / Hyperspectral imaging (HSI) extends from the fact that for any given material, the amount of emitted radiation varies with wavelength. HSI sensors measure the radiance of the materials within each pixel area at a very large number of contiguous spectral bands and provide image data containing both spatial and spectral information. Classical adaptive detection schemes assume that the background is zero-mean Gaussian or with known mean vector that can be exploited. However, when the mean vector is unknown, as it is the case for hyperspectral imaging, it has to be included in the detection process. We propose in this work an extension of classical detection methods when both covariance matrix and mean vector are unknown.However, the actual multivariate distribution of the background pixels may differ from the generally used Gaussian hypothesis. The class of elliptical distributions has already been popularized for background characterization in HSI. Although these non-Gaussian models have been exploited for background modeling and detection schemes, the parameters estimation (covariance matrix, mean vector) is usually performed using classical Gaussian-based estimators. We analyze here some robust estimation procedures (M-estimators of location and scale) more suitable when non-Gaussian distributions are assumed. Jointly used with M-estimators, these new detectors allow to enhance the target detection performance in non-Gaussian environment while keeping the same performance than the classical detectors in Gaussian environment. Therefore, they provide a unified framework for target detection and anomaly detection in HSI.

Les ports maritimes se confrontent à des exigences rigoureuses imposées par l'évolution de la taille de la flotte mondiale des porte-conteneurs et des zones de stockage qui arrivent à des niveaux de saturation élevés. Pour répondre à ces défis, plusieurs ports ont décidé de créer des terminaux multimodaux qui jouent le rôle de méga-hubs pour les terminaux maritimes, en vue de libérer les zones de stockage de ces terminaux, de développer la part du transport massifié de conteneurs et de réduire les émissions des gaz à effet de serre en utilisant des modes alternatifs à la route. Néanmoins, la gestion de ces nouveaux schémas logistiques est laborieuse. Cela s’explique par plusieurs facteurs, entre autres, la nature dynamique et distribuée de ces systèmes, la diversité des opérations et le manque des informations nécessaires au contrôle de flux. La finalité de cette thèse est de développer des approches capables de répondre aux besoins des opérateurs portuaires dans un terminal multimodal, avec prise en compte des différentes sources d’incertitudes. Deux problèmes d'optimisation sont principalement considérés dans cette thèse, à savoir : l'optimisation de tournées de navettes ferroviaires (The Rail Shuttle Routing Problem) et l'ordonnancement de grues de quai (The Quay Crane Scheduling Problem). En vue d'aborder la complexité et l’aspect incertain de ces problèmes, nous proposerons des modélisations mathématiques, ainsi que des approches de résolution basées sur l’optimisation par colonies de fourmis, l’optimisation robuste et le couplage Simulation-Optimisation. Les différents tests numériques effectués ont prouvé l’efficacité des algorithmes proposés et leur robustesse. / Today, seaports face increasingly stringent requirements imposed by the considerable growth of goods transited by sea. Indeed, the organization of the port sector has evolved rapidly and has caused several negative impacts, including pollution and congestion of terminals, which constitute today the major concerns of port operators. To address those challenges, several ports have decided to build multimodal terminals that act as mega-hubs for maritime terminals, in order to free the storage areas on the maritime terminals, to promote the use of consolidated container modes of transfer and to reduce greenhouse gas emissions by using alternative modes to the road. Nevertheless, the management of these new logistic systems is laborious. This is due to several factors, including the dynamic and distributed nature of these systems, the variety of operations, and the lack of information needed to control flow. The aim of this thesis is to develop approaches capable of meeting the needs of port operators in a multimodal terminal, taking into account the different sources of uncertainty. Two optimization problems are mainly considered in this thesis, namely : the Rail Shuttle Routing Problem(RSRP) and the Quay Crane Scheduling Problem(QCSP). To address the complexity and uncertainties of these problems, we propose new mathematical models, as well as some heuristics approaches based on ant colony optimization, robust optimization and Simulation-Optimization. The various numerical tests carried out proved the effectiveness and the robustness of the proposed algorithms.

La surveillance des nouveau-nés prématurés placés en unité de soins intensifs a conduit à la notion de monitoring et à l'acquisition de nombreux signaux physiologiques. Si ces informations sont bien utilisées pour le diagnostic et la prévention des situations d'urgence, force est de constater qu'à ce jour, elles le sont beaucoup moins dans un objectif prédictif. La difficulté d'extraction d'informations fiables en temps réel, sans aucun contrôle visuel, à partir de signaux non stationnaires, en est vraisemblablement la cause. Ce mémoire vise donc à proposer des méthodes robustes, adaptées au contexte des unités de soins intensifs néonatals et du temps réel. Pour cela, un ensemble de méthodes génériques appliquées à la variabilité cardiaque, mais capable d'être adaptées à d'autres constantes physiologiques telles que la respiration, ont été développées et testées en contexte clinique. Quatre grandes parties illustrent notre propos : - La proposition d'une méthode originale de détection temps réel probabiliste multicaractéristique permettant de répondre à une problématique d'extraction robuste d'événements d'intérêt à partir de signaux physiologiques bruités. Générique, cette solution est appliquée à la détection robuste du QRS d'un signal ECG. Elle est basée sur le calcul temps réel de plusieurs probabilités a posteriori, concernant les propriétés du signal, qui sont ensuite fusionnées au sein d'un nœud de décision reposant sur l'utilisation pondérée de la divergence de Kullback-Leibler. Comparée à deux méthodes classiques de la littérature sur deux bases de données bruitées, elle obtient un taux d'erreur de détection inférieur (20.91% vs 29.02% (ondelettes) et 33.08% (Pan-Tompkins) sur la base de test). - La proposition d'une méthode impliquant plusieurs modèles semi-markoviens cachés, visant la segmentation de périodes au sein desquelles le détecteur temps réel probabiliste multicaractéristique fournit les détections d'évènements les plus fiables. En comparaison à deux méthodes de la littérature, la solution proposée obtient de meilleures performances, le critère d‘erreur obtenu est significativement plus faible (entre -21.37% et -74.98% selon la base et l'approche évaluée). - La sélection d'un détecteur optimal pour le monitoring d'événements d'apnée-bradycardie, en termes de fiabilité et précocité, à partir de données ECG obtenues chez le nouveau-né. Les performances du détecteur retenu seront comparées aux alarmes générées par un dispositif industriel de suivi continu classiquement utilisé en service de néonatalogie (moniteur Philips IntelliVue). La méthode basée sur le changement abrupt de la moyenne des RR obtient les meilleurs résultats au regard du délai (3.99 s vs 11.53 s pour le moniteur IntelliVue) et de la fiabilité (critère d'erreur de 43.60% vs 80.40%). - La conception et le développement d'une plateforme logicielle SYNaPSE (SYstem for Noninvasive Physiological Signal Explorations) permettant l'acquisition de divers signaux physiologiques en très grande quantité, et de façon non invasive, au sein des unités de soins. La conception modulaire de cette plateforme, ainsi que ses propriétés temps réel, permettent l'intégration simple et rapide de méthodes de traitement du signal complexes. Son intérêt translationnel est montré dans le dépouillement d'une base de données cherchant à étudier l'impact de la bilirubine sur la variabilité cardiaque. / The surveillance of premature newborns placed in intensive care units led to the notion of monitoring and the acquisition of many physiological signals. While this information is well used for the diagnosis and prevention of emergency situations, it must be acknowledged that, to date, it is less the case for predictive purposes. This is mainly due to the difficulty of extracting reliable information in real time, without any visual control, from non-stationary signals. This thesis aims to propose robust methods, adapted to the context of neonatal intensive care units and real time. For this purpose, a set of generic methods applied to cardiac variability, but capable of being adapted to other physiological constants such as respiration, have been developed and tested in clinical context. Four main parts illustrate these points : - The proposal of an original multicharacteristic probabilistic real time detection method for robust detection of interest events of noisy physiological signals. Generic, this solution is applied to the robust QRS complex detection of the ECG signals. It is based on the real time calculation of several posterior probabilities of the signal properties before merging them into a decision node using the weighted Kullback-Leibler divergence. Compared to two classic methods from the literature on two noisy databases, it has a lower detection error rate (20.91% vs. 29.02% (wavelets) and 33.08% (Pan-Tompkins) on the test database). - The proposal of using hidden semi-markovian models for the segmentation of temporal periods with most reliable event detections. Compared to two methods from the literature, the proposed solution achieves better performance, the error criterion obtained is significantly lower (between -21.37% and -74.98% depending on the basis and approach evaluated). - The selection of an optimal detector for the monitoring of apnea-bradycardia events, in terms of reliability and precocity, based on ECG data obtained from newborns. The performance of the selected detector will be compared to the alarms generated by an industrial continuous monitoring device traditionally used in neonatology service (Philips IntelliVue monitor). The method based on the abrupt change of the RR average achieves the best results in terms of time (3.99 s vs. 11.53 s for the IntelliVue monitor) and reliability (error criterion of 43.60% vs. 80.40%). - The design and development of SYNaPSE (SYstem for Noninvasive Physiological Signal Explorations) software platform for the acquisition of various physiological signals in large quantities, and in a non-invasive way, within the care units. The modular design of this platform, as well as its real time properties, allows simple and fast integration of complex signal processing methods. Its translational interest is shown in the analysis of a database in order to study the impact of bilirubin on cardiac variability.

Acknowledging the goal of reduced aircraft weight, there is a need to improve on conservative design techniques used in industry. Minimisation of laminate in-plane elastic energy is used as an appropriate in-plane performance marker to assess the weight saving potential of new design techniques. MATLAB optimisations using a genetic algorithm were used to find the optimal laminate variables for minimum in-plane elastic energy and/or damage tolerance for all possible loadings. The use of non-standard angles was able to offer equivalent, if not better in-plane performance than standard angles, and are shown to be useful to improve the ease of manufacture. Any standard angle laminate stiffness was shown to be able to be matched by a range of two non-standard angle ply designs. This non-uniqueness of designs was explored. Balancing of plus and minus plies about the principal loading axes instead of themanufacturing axes was shown to offer considerable potential for weight saving as the stiffness is better aligned to the load. Designing directly for an uncertain design load showed little benefit over the 10% ply percentage rule in maintaining in-plane performance. This showed the current rule may do a sufficient job to allow robustness in laminate performance. This technique is seen useful for non-standard angle design that lacks an equivalent 10% rule. Current use of conservative damage tolerance strain limits for design has revealed the need for more accurate prediction of damage propagation. Damage tolerance modelling was carried out using fracture mechanics for a multi-axial loading considering the full 2D strain energy and improving on current uni-axial models. The non-conservativeness of the model was evidenced to be from assumptions of zero post-buckled stiffness. Preliminary work on conservative multi-axial damage tolerance design, independent of thickness, is yet to be confirmed by experiments.

In this thesis, we present some contributions to the Markov jump linear systems theory in a context of partial information on the Markov chain. We consider that the state of the Markov chain cannot be measured, but instead there is only an observed variable that could model an asynchronous phenomenon between the application and the plant, or a simple fault detection and isolation device. In this formulation, we investigate the problem of designing controllers and filters depending only on the observed variable in the context of H2, H?, and mixed H2/H? control theory. Numerical examples and academic applications are presented for active-fault tolerant control systems and networked control systems. / Nesta tese, apresentamos algumas contribuições para a teoria de sistemas lineares com saltos markovianos em um contexto de observação parcial da cadeia de Markov. Consideramos que o estado da cadeia de Markov não pode ser medido, porém existe uma variável observada que pode modelar um fenômeno assíncrono entre a aplicação e a planta, ou ainda um dispositivo de detecção de falhas simples. Através desse modelo, investigamos o problema da síntese de controladores e filtros que dependem somente da variável observada no contexto das teorias de controle H2, H?, e misto H2/H?. Exemplos numéricos e aplicações acadêmicas são apresentadas no âmbito dos sistemas de controle tolerantes a falhas e dos sistemas de controle através da rede.