Nesta tese de doutorado são apresentados sistemas globais de estimativa baseados em modelos Markovianos aplicados na área de reabilitação robótica. Os sistemas propostos foram desenvolvidos para estimar as posições angulares dos elos de exoesqueletos para membros inferiores, desenvolvidos para reabilitação motora em pacientes que sofreram Acidente Vascular Cerebral (AVC) ou lesão medular. Filtros baseados no filtro de Kalman, um nominal e outro considerando incertezas no modelo, foram utilizados em estratégias de fusão de dados de sensores provenientes de sensores inerciais, possibilitando estimativas de posicionamentos angulares. Algoritmos genéticos são utilizados na otimização dos filtros, ajustando as matrizes de peso destes. Em oposição as modelagens tradicionais, via estimativa local, utilizando somente uma unidade inercial para cada modelo, propõe-se um sistema global de estimativa, obtendo-se a melhor informação de cada sensor combinando-os em um modelo Markoviano. Resultados experimentais com um exoesqueleto foram utilizados para comparar a abordagem Markoviana às convencionais. / In this thesis are presented global estimation systems based on Markov models applied in robotic rehabilitation area. The proposed systems have been developed to estimate the angular positions of the exoskeletons for lower limbs, designed to provide motor rehabilitation of stroke and spinal cord injured people. Filters based on the Kalman filter, one nominal and other considering uncertainties in the model, were used in sensor data fusion strategies from inertial sensors, to estimate angular positions. Genetic algorithms are used to the optimization of filters, tuning the weighting matrices. In opposition to these modelling via local estimation, using only one inertial unit, we also chose a global modelling getting the best information from each sensor, combining them in a Markov model. Experimental results with an exoskeleton were used to compare the Markovian approach to conventional.

Control of systems requiring direct physical human-robot interaction (pHRI) requires special consideration of the motion, dynamics, and control of both the human and the robot. Humans actively change their dynamic characteristics during motion, and robots should be designed with this in mind. Both the case of humans trying to control haptic robots using physical contact and the case of using wearable robots that must work with human muscles are pHRI systems. Force feedback haptic devices require physical contact between the operator and the machine, which creates a coupled system. This human contact creates a situation in which the stiffness of the system changes based on how the operator modulates the stiffness of their arm. The natural human tendency is to increase arm stiffness to attempt to stabilize motion. However, this increases the overall stiffness of the system, making it more difficult to control and reducing stability. Instability poses a threat of injury or load damage for large assistive haptic devices with heavy loads. Controllers do not typically account for this, as operator stiffness is often not directly measurable. The common solution of using a controller with significantly increased controller damping has the disadvantage of slowing the device and decreasing operator efficiency. By expanding the information available to the controller, it can be designed to adjust a robot's motion based on the how the operator is interacting with it and allow for faster movement in low stiffness situations. This research explored the utility of a system that can estimate operator arm stiffness and compensate accordingly. By measuring muscle activity, a model of the human arm was utilized to estimate the stiffness level of the operator, and then adjust the gains of an impedance-based controller to stabilize the device. This achieved the goal of reducing oscillations and increasing device performance, as demonstrated through a series of user trials with the device. Through the design of this system, the effectiveness of a variety of operator models were analyzed and several different controllers were explored. The final device has the potential to increase the performance of operators and reduce fatigue due to usage, which in industrial settings could translate into better efficiency and higher productivity. Similarly, wearable robots must consider human muscle activity. Wearable robots, often called exoskeleton robots, are used for a variety of tasks, including force amplification, rehabilitation, and medical diagnosis. Force amplification exoskeletons operate much like haptic assist devices, and could leverage the same adaptive control system. The latter two types, however, are designed with the purpose of modulating human muscles, in which case the wearer's muscles must adapt to the way the robot moves, the reverse of the robot adapting to how the human moves. In this case, the robot controller must apply a force to the arm to cause the arm muscles to adapt and generate a specific muscle activity pattern. This related problem is explored and a muscle control algorithm is designed that allows a wearable robot to induce a specified muscle pattern in the wearer's arm. The two problems, in which the robot must adapt to the human's motion and in which the robot must induce the human to adapt its motion, are related critical problems that must be solved to enable simple and natural physical human robot interaction.

The purpose of this thesis is to explore the subject of industrial exoskeleton in accord-ance to the applicability of the technology preventing musculoskeletal disorders within the automotive industry. The modern technology of exoskeletons has a limited field of research and knowledge and is in need to be studied to provide organisations with proper findings for understanding the applicability of the technology. In the auto-motive industry musculoskeletal disorders (MSDs) is one of the most common disor-ders among employees and industries work constantly to decrease and prevent MSDs within their work environments. By conducting literature reviews, the status of exo-skeleton research and development concluded that academic research mostly focuses on technological development of exoskeletons, and not laboratory and/or field testing of currently available industrial exoskeletons. However, through database and website searches, twenty-four available industrial exoskeletons were identified which could be applicable within the automotive industry. Through literature and a case illustration, a number of potential causes for MSDs within the automotive industry were identified and a framework was developed in order to match appropriate available industrial ex-oskeleton to be used in potentially preventing common MSDs. The discussion of the thesis highlights the benefits and challenges of implementing an industrial exoskele-ton within an industry. Proper research on the currently available industrial exoskele-tons is lacking and creates questions of reliability for the technology. However, devel-opment of industrial exoskeletons have shown to focus on prevention of the most common causes of MSDs within industries in their design and development, making the applicability of industrial exoskeletons highly possible.

Ce projet s’inscrit dans l’effort développé par l’Agence Spatiale Européenne (ESA)pour robotiser les activités extravéhiculaires à bord de la Station Spatiale Internationale et lors des futures missions d’exploration planétaire. Un aspect important de ces projets concerne le retour de force et la capacité, pour la personne qui commande les mouvements du robot, à ressentir les efforts qui lui sont appliqués. Le but est d’améliorer la qualité et l’immersion de la téléopération.<p><p>L’objectif de cette thèse est la conception d’une interface haptique de type exosquelette pour le bras, pour ces missions de téléopération à retour de force. Ce système doit permettre une commande intuitive du robot téléopéré tout en reproduisant<p>le plus fidèlement possible les efforts. <p><p>Les chapitres 2 et 3 présentent les études réalisées sur un banc de test à 1 degré de liberté, destinées à comprendre le contrôle haptique ainsi qu’à évaluer différentes technologies d’actionnements et de capteurs. Les principales méthodes de contrôle sont décrites théoriquement et comparées en pratique sur le banc de test. Les<p>chapitres 4 et 5 décrivent le développement de l’exosquelette SAM destiné aux futures applications de téléopération spatiale. La conception cinématique, le choix des actionneurs et des capteurs sont décrits. Différentes méthodes de contrôle sont également comparées avec des expériences de réalité virtuelle (sans robot esclave) et de téléopération. Pour finir, le chapitre 6 présente le projet EXOSTATION, un démonstrateur de téléopération haptique spatiale, dans lequel SAM est utilisé comme interface maître. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

Este trabalho apresenta o desenvolvimento de algoritmos de adaptação do padrão de marcha com a utilização de redes neurais artificiais para uma órtese ativa para membros inferiores. Trajetórias estáveis são geradas durante o processo de otimização, considerando um gerador de trajetórias baseado no critério do ZMP (Zero Moment Point) e no modelo dinâmico do equipamento. Três redes neurais são usadas para diminuir o tempo de cálculo do modelo e da otimização do ZMP, e reproduzir o gerador de trajetórias analítico. A primeira rede aproxima a dinâmica do modelo fornecendo a variação de torque necessária para a realização do processo de otimização dos parâmetros de adaptação da marcha; a segunda rede trabalha no processo de otimização, fornecendo o parâmetro otimizado de acordo com a interação paciente-órtese; a terceira rede reproduz o gerador de trajetórias para um determinado intervalo de tempo do passo que pode ser repetido para qualquer quantidade de passos. Além disso, um controle do tipo torque calculado acrescido de um controle PD é usado para garantir que as trajetórias atuais estejam seguindo as trajetórias desejadas da órtese. O modelo dinâmico da órtese na sua configuração atual, com forças de interação incluídas, é usado para gerar resultados simulados. / This work deals with neural network-based gait-pattern adaptation algorithms for an active lower limbs orthosis. Stable trajectories are generated during the optimization process, considering a trajectory generator based on the Zero Moment Point criterion and on the dynamic model. Additionally, three neural network are used to decrease the time-consuming computation of the model and ZMP optimization and to reproduce the analitical trajectory generator. The first neural network approximates the dynamic model providing the necessary torque variation to gait adaptation parameters process; the second network works in the optimization procedure, giving the adapting parameter according to orthosis-patient interaction; and the third network replaces the trajectory generation for a stablished step time interval which can be reproduced any time during the walking. Also, a computed torque controller plus the PD controller is designed to guarantee the actual trajectories are following the orthosis desired trajectories. The dynamic model of the actual active orthosis, with interaction forces included, is used to generate simulation results.

La robotique constitue une solution prometteuse pour développer des systèmes d'assistance visant à améliorer l'autonomie et les conditions de vie des personnes dépendantes. Ainsi, de nombreuses recherches sont menées actuellement à travers le monde pour concevoir et développer des robots portables ou exosquelettes, en tant que dispositifs d'aide à la mobilité pour augmenter les capacités motrices des sujets porteurs, ou comme auxiliaires de rééducation neuro-musculaire. Cette thèse vise le développement des modèles de connaissances nécessaires pour la mise en oeuvre de commandes assistives d'un exosquelette de l'articulation du genou, notamment celles basées sur l'intention du sujet porteur. Cet exosquelette est destiné à l'assistance des mouvements de flexion/extension du genou pour des personnes souffrant de pathologies du genou, ou pour le renforcement musculaire et la rééducation de sujets âgés ou hémiparétiques. Pour l'estimation de l'intention de mouvement du porteur, nous proposons modèle musculo-squelettique polynomial, complété par un modèle muscle-tendons de type Hill et le modèle bi-linéaire de Zajac pour modéliser la dynamique d'activation et de désactivation musculaire. Le modèle musculo-squelettique polynomial proposé offre le même niveau de réalisme et de précision qu'un modèle musculo-squelettique générique anatomique, sans nécessiter l'emploi de méthodes d'optimisation gourmandes en temps de calcul. Dans cette thèse, nous proposons un ensemble de trois commandes assistives destinées à guider ou à assister, via l'exosquelette, un sujet dans un contexte d'assistance à la rééducation en mode actif-aidé: La première, basée sur la passivité, exploite les propriétés physiques de l'exosquelette et du sujet porteur pour stabiliser asymptotiquement l'ensemble exosquelette-membre inférieur du porteur. Les paramètres du contrôleur sont ajustés automatiquement en fonction de la contribution du sujet au mouvement. A travers cette commande, l'exosquelette développe un couple correctif pour guider le genou vers la trajectoire de référence ou son voisinage. La seconde commande introduit une saturation pour maintenir le couple d'assistance dans un intervalle donné, garantissant ainsi la sécurité du sujet porteur. Cette commande garantit aussi des mouvements à des vitesses raisonnables et une convergence vers la trajectoire de référence. La deuxième loi de commande est complétée par une fonction permettant de moduler le couple d'assistance en fonction de la phase de rééducation. Enfin, la troisième commande proposée vise à maximiser la transparence de l'exosquelette pour éviter d'altérer les mouvements naturels du sujet porteur. Elle exploite la dynamique d'interaction induite par les mouvements relatifs du sujet porteur par rapport à l'exosquelette dus aux compliances intrinsèques de l'ensemble exosquelette-membre inférieur. Ces commandes ont été évaluées sur un sujet volontaire sain âgé de 29 ans, en considérant les modes d'assistance passif et actif-aidé. L'analyse des résultats expérimentaux montre de bonnes performances en termes de précision de poursuite de trajectoire, de robustesse vis-à-vis des incertitudes paramétriques et des perturbations externes. Ces résultats montrent également des propriétés importantes comme la sécurité du sujet porteur, le suivi précis de l'intention du porteur, l'assistance adaptative pour la rééducation active et la transparence de l'interaction exosquelette-porteur / Nowadays, robotics constitutes a promising solution to develop assistive systems to improve autonomy of dependent people during everyday activities. Thus, much research is being conducted currently worldwide to design and develop wearable robots or exoskeletons as assistive devices for mobility in order to improve the capabilities of the wearer. These devices can also be used during neuromuscular rehabilitation processes. This thesis aims to develop models necessary for the implementation of subject's intention wearer assistive control strategies using a knee joint exoskeleton. In order to estimate the movement intention of the wearer, we propose a Hill- Zajac based musculoskeletal model. This musculoskeletal model provides a high level of realism and accuracy compared to an anatomical generic musculoskeletal model without requiring the use of optimization methods techniques that are generally computational effort consuming. Three assistive control strategies are developed in this thesis to assist the wearer in a context of assistance and rehabilitation. In this thesis, we propose a set of three assistive commands to guide or assist through the exoskeleton, a subject in the context of rehabilitation assistance to active-assisted method: The first, based on passivity, operates the physical properties of the exoskeleton about the wearer and to stabilize the lower assembly asymptotically exoskeleton-member carrier. The first one is based on passivity and uses the physical properties of the exoskeleton and the wearer to stabilize asymptotically the human- lower-limb exoskeleton system. The second one introduces a saturation threshold to maintain the assistive torque in a given interval, ensuring the safety of the wearer. The third one aims to maximize the transparency of the exoskeleton to avoid altering the natural movements of the wearer. It uses the interaction dynamics induced by the relative movements between the wearer and the exoskeleton. These control strategies were evaluated on a 29-year-old healthy volunteer subject. The analysis of the experimental results shows satisfactory performances in terms of trajectory tracking accuracy, robustness with respect to parametric uncertainties and external disturbances. The results show also a good accuracy in the human intention detection and an adaptive support for active rehabilitation and transparent human-robot interaction

Le sujet de thèse concerne le développement de l'architecture de contrôle et la génération de trajectoire pour un exosquelette évolutif appelé SOL. Les résultats de l'étude biomédicale ont révélé que la progressivité de la maladie pouvait être résolue par une réadaptation précoce et continue tout au long de la croissance. Ainsi, l'importance de l'utilisation d'un exosquelette a un impact positif puisqu'il sert à la fois à la locomotion et à la réhabilitation. Cependant, les exosquelettes actuels ne peuvent pas être adaptés au changement continu de la biomécanique de l'adolescent tout au long de sa croissance. Par conséquent, le besoin de développer un exosquelette évolutif capable de faire face aux besoins croissants est un sujet interdisciplinaire. L'architecture de contrôle d'un tel dispositif évolutif a été abordée dans cette thèse, à la fois dans les développements matériels et logiciels pour incorporer autant que possible la fonctionnalité d'évolutivité. Les étapes initiales ont été franchies en vue d'atteindre l'objectif d'un exosquelette évolutif, en contribuant à la fois aux développements matériels qui permettent d'apporter d'autres améliorations tout au long de l'avancement du projet, et aux développements du firmware, qui ont répondu aux besoins en matière d'évolutivité au niveau du contrôle.L'extensibilité a également été abordée aux trois niveaux hiérarchiques de contrôle. Plus spécifiquement, une attention particulière a été accordée à la génération des trajectoires de référence de la marche pour une population en croissance. Enfin, grâce à la connaissance de la biomécanique du sujet, le contrôleur développé est capable d’identifier les trajectoires appropriées et injecter les trajectoires de référence des actionneurs de l’exosquelette SOL.Un premier prototype de l'exosquelette est utilisé pour manifester les résultats du générateur de marche évolutionnaire (E.G.G.) proposé. Comme premier prototype, un mouvement de marche libre dans l'air est testé, où la validation du matériel proposé et des boucles de contrôle sont démontrées. L'étude des réponses de contrôle des exosquelettes contre les perturbations externes probables et des scénarios de sécurité en cas de défaillance est encore un travail futur obligatoire avant de réaliser les premiers tests sur l'exosquelette humain. / The thesis' subject concerns the development of the control architecture and the trajectory generation for a scalable exoskeleton called SOL. The biomedical study outcomes revealed that the progressiveness of the disease could be solved by early and continuous rehabilitation throughout the growth. Thus, the importance of using an exoskeleton has a positive impact since it is used to provide locomotion and rehabilitation, at the same time. However, the current exoskeletons cannot be adapted to fit the continuous change of teenager biomechanics throughout his growth. Hence, the need for developing a scalable exoskeleton that can cope with the growing needs is still a challenging topic. Especially, the control architecture of such a scalable device was tackled in this thesis, in both hardware and software developments to incorporate the scalability features. Initiative steps have been passed towards the goal of achieving a scalable exoskeleton, by contributing in hardware developments that allowing further enhancements to be included throughout the advancement of the project. Firmware developments achieved have addressed the scalability needs in terms of control by considering the three hierarchical levels (which are: High, Middle, and low-levels of control). More specifically, a focus was dedicated to the generation of the gait reference trajectories for the growing population. Data were collected from healthy subjects wearing a passive exoskeleton to extract the proper joint trajectories, then, the data were processed to build a gait library to be deployed on the exoskeleton controller. Finally, by knowledge of the subject biomechanics, the controller is able to fetch the proper trajectories and inject the reference trajectories to the SOL's actuators. A first prototype of the exoskeleton is used to manifest the outcomes of the proposed Evolutionary Gait Generator (E.G.G.). As a first prototype, A free walking in air motion is tested, where the validation of the proposed hardware and control loops are demonstrated. Studying the exoskeletons' control responses against probable external disturbances and fail-safe scenarios are still future work mandatory before achieving first human-exoskeleton testing.

No description available.

Robotic exoskeletons are designed to assist patients with motor dysfunctions. Recent researches focus on extending the robotic assistance to patient activities other than ground level walking. This study aims to analyse the lower limb muscle activity during inclined slope walking contrasting with that of ground level walking. Two different angles of inclination were chosen: 9 degrees and 18 degrees. 9 degrees inclined slope is the universal ramp size for wheelchairs. The hypothesis is that muscle activation, and ultimately metabolic cost, in inclined slope walking is different from that of ground level walking. Collected motion data and simulation in OpenSim prove that the difference in metabolic cost is because of increased activity of ankle dorsiflexors and hip extensors and reduced activity of knee extensors. Finally, muscle activities along with other criteria such as kinematic alignment and joint range of motion are summed up as biomechanical considerations for robotic exoskeleton design.

This thesis presents an activity mode intent recognition approach for safe, robust and reliable control of powered backbone exoskeleton. The thesis presents the background and a concept for a powered backbone exoskeleton that would work in parallel with a user. The necessary prerequisites for the thesis are presented, including the collection and processing of surface electromyography signals and inertial sensor data to recognize the user’s activity. The development of activity mode intent recognizer was described based on decision tree classification in order to leverage its computational efficiency. The intent recognizer is a high-level supervisory controller that belongs to a three-level control structure for a powered backbone exoskeleton. The recognizer uses surface electromyography and inertial signals as the input and CART (classification and regression tree) as the classifier. The experimental results indicate that the recognizer can extract the user’s intent with minimal delay. The approach achieves a low recognition error rate and a user-unperceived latency by using sliding overlapped analysis window. The approach shows great potential for future implementation on a prototype backbone exoskeleton.