Robotic arms and hands come in all shapes and sizes, they can be general purpose or task-specific. They can be pre-programed by a computer or controlled by a human operator. There is a certain subsection of robotic hands which try to mimic the shape, movement and function of the human hand, these are sometimes known as biomimetic robotics. This project explores the human robot interaction by creating an anthropomorphic robotic hand with an accompanying exoskeleton. The hand, which consists of a 3D-printed body and fingers, is connected to a forearm where the servos that control the fingers are housed. The exoskeleton connects to the operator's hand allowing finger tracking through a set of potentiometers. This setup allows the operator to intuitively control a robotic hand with a certain degree of precision. We set out to answer research questions in regard to the form and function of a biomimetic hand and the exoskeleton. Along the way, a multitude of problems were encountered such as budgetary issues resulting in only half the fingers having movement. Despite this, good results were gathered from the functioning fingers and our research questions were answered. / Robotarmar och händer finns många former och storlekar, de kan vara för allmänna ändamål eller uppgiftsspecifika. De kan programmeras av en dator eller styras av en mänsklig operatör. Det finns en viss typ av robothänder som försöker efterlikna formen, rörelsen och funktionen hos den mänskliga handen, och brukar kallas biomimetisk robotik. Detta projekt utforskar interaktionen mellan människa och robot genom att skapa en antropomorf robothand med tillhörande exoskelett. Handen, som består av en 3D-printad kropp och fingrar, är ansluten till en underarm där servormotorerna som styr fingrarna sitter. Exoskelettet ansluts till operatörens hand vilket möjliggör spårning av fingrarnas rörelse genom ett antal potentiometrar. Detta tillåter operatören att intuitivt styra en robothand med en viss grad av precision. Vi valde att besvara ett antal forskningsfrågor med avseende på form och funktion av en biomimetisk hand och exoskelettet. Under projektets gång påträffades en mängd problem såsom budgetproblem som resulterade i att bara hälften av fingrarna kan kontrolleras. Trots detta fick vi bra resultat från de fungerande fingrarna och våra forskningsfrågor kunde besvaras.

The hands and feet account for half of the complexity of the musculoskeletal system, while the skin of the hand is specialised with many important structures. Much of the subtlety of the mechanism of the hand lies in the soft tissues, and the tactile and proprioceptive sensitivity depends on the large number of mechanoreceptors embedded in specific structures of the soft tissues. This thesis investigates synthetic materials and manufacturing techniques to enable building robots that reproduce the biomechanics and tactile sensitivity of vertebrates – histomimetic robotics. The material and mechanical anatomy of the hand is reviewed, highlighting difficulty of numerical measurement in soft-tissue anatomy, and the predictive nature of descriptive anatomical knowledge. The biomechanical mechanisms of the hand and their support of sensorimotor control are presented. A palate of materials and layup techniques are identified for emulating ligaments, joint surfaces, tendon networks, sheaths, soft matrices, and dermal structures. A method for thermoplastically drawing fine elastic fibres, with liquid metal amalgam cores, for connecting embedded sensors is demonstrated. The performance requirements of skeletal muscles are identified. Two classes of muscle-like bulk MEMS electrostatic actuators are shown theoretically to be capable of meeting these requirements. Means to manufacture them, and their additional application as mechanoreceptors are described. A novel machine perception algorithm is outlined as a solution to the problem of measuring soft tissue anatomy, CAD/CAE/CNC for layup of histomimetic robots, and sensory perception by such robots. The results of the work support the view that histomimetic robotics is a viable approach, and identify a number of areas for further investigation including: polymer modification by graft-polymerisation, automated layup tools, and machine perception.

Le sujet principal de cette thèse est le développement d’un contrôle commande intelligentpour une prothèse de main robotique avec des parties souples qui comporte: (i) uneinterface homme–machine permettant de contrôler notre prothèse, (ii) et des stratégiesde contrôle améliorant les performances de la main robotique. Notre approche tientcompte : 1. du développement d’une interaction intuitive entre l'homme et la prothèse facilitantl'utilisation de la main, d'un système d’interaction entre l’utilisateur et la mainreposant sur l'acquisition de signaux ElectroMyoGrammes superficiels (sEMG) aumoyen d'un dispositif placé sur l'avant-bras du patient. Les signaux obtenus sontensuite traités avec un algorithme basé sur l'intelligence artificielle, en vued'identifier automatiquement les mouvements désirés par le patient.2. du contrôle de la main robotique grâce à la détection du contact avec l’objet et de lathéorie du contrôle hybride.Ainsi, nous concentrons notre étude sur : (i) l’établissement d’une relation entre lemouvement du membre supérieur et les signaux sEMG, (ii) les séparateurs à vaste margepour classer les patterns obtenues à partir des signaux sEMG correspondant auxmouvements de préhension, (iii) le développement d'un système de reconnaissance depréhension à partir d'un dispositif portable MyoArmbandTM, (iv) et des stratégieshybrides de contrôle commande de force-position de notre main robotique souple. / The target of this thesis disertation is to develop a new Smart control of a soft robotic hand prosthesis for the soft robotic hand prosthesis called ProMain Hand, which is characterized by:(i) flexible interaction with grasped object, (ii) and friendly-intuitive interaction between human and robot hand. Flexible interaction results from the synergies between rigid bodies and soft bodies, and actuation mechanism. The ProMain hand has three fingers, each one is equipped with three phalanges: proximal, medial and distal. The proximal and medial are built with rigid bodies,and the distal is fabricated using a deformable material. The soft distal phalange has a new smart force sensor, which was created with the aim to detect contact and force in the fingertip, facilitating the control of the hand. The friendly intuitive human-hand interaction is developed to facilitate the hand utilization. The human-hand interaction is driven by a controller that uses the superficial electromyographic signals measured in the forearm employing a wearable device. The wearable device called MyoArmband is placed around the forearm near the elbow joint. Based on the signals transmitted by the wearable device, the beginning of the movement is automatically detected, analyzing entropy behavior of the EMG signals through artificial intelligence. Then, three selected grasping gesture are recognized with the following methodology: (i) learning patients entropy patterns from electromyographic signals captured during the execution of selected grasping gesture, (ii) performing a support vector machine classifier, using raw entropy data extracted in real time from electromyographic signals.

Submitted by Maike Costa (maiksebas@gmail.com) on 2017-05-24T14:46:36Z No. of bitstreams: 1 arquivototal.pdf: 13879425 bytes, checksum: b7216c05b85b83f1b7adc4577ae083ba (MD5) / Made available in DSpace on 2017-05-24T14:46:36Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 13879425 bytes, checksum: b7216c05b85b83f1b7adc4577ae083ba (MD5) Previous issue date: 2015-08-28 / This work is based on studies that prove a great rejection rate by amputees on using prosthetic upper limbs due to various problems, such as weight, high noise and lack of anthropomorphism. In this context, this paper presents the development of a robotic hand drive which is not realized by conventional actuators, constituted of wires of a shape memory alloy (SMA). The mechanical structure of the robot hand was designed in CAD software and subsequently manufactured with ABS polymer through rapid prototyping using a three-dimensional printer. The project was designed partially based on the physiological characteristics of the human hand, regarding especially to the angles formed by fingers’ phalanges. A mechanical system was developed in order to compactly accommodate the thin wires of a NiTi SMA, known in this work as Artificial Muscle (AM) which made the compression of SMA wires easier. The performance (operation) of the fingers occurs by the AM activation that are connected to cables arranged in the lower part of the fingers’ structure, which, when activated, perform the movement of flexion. The return of each phalanx, or extension movement of the fingers occurs passively. Elastic elements were installed in the upper part of the phalanges which are responsible for this movement. To monitor the angles formed by each phalanx was used a resistive type sensor that is inserted inside it, varying its electric resistance according to angle variation. On top of this system, a fuzzy logic based controller was developed and it proved to be effective on monitoring the position of the robotic hand’s fingers. The performance of the robot hand can be considered appropriate, as it could partially achieve the desired angles based on the project design. / Este trabalho está fundamentado em estudos que comprovam o grande índice de rejeição por parte de pessoas amputadas ao utilizarem próteses de membros superiores devido a problemas diversos, tais como: peso, ruído elevado e falta de antropomorfismo. Nesse contexto, neste trabalho é apresentado o desenvolvimento de uma mão robótica cujo acionamento é realizado por atuadores não convencionais, constituídos de fios de uma Liga com Memória de Forma (LMF). A estrutura mecânica da mão robótica foi projetada em programa computacional CAD e posteriormente fabricada em polímero ABS por meio de prototipagem rápida usando uma impressora tridimensional. O projeto foi concebido parcialmente com base nas características fisiológicas da mão humana, no que diz respeito principalmente aos ângulos formados pelas falanges dos dedos. Foi desenvolvido um sistema mecânico para acondicionar os fios finos de uma LMF de Ni-Ti de forma compacta denominado neste trabalho por Músculo Artificial (MA) o que facilitou a compactação dos fios de LMF. A atuação dos dedos ocorre pela ativação dos MA que estão conectados a cabos dispostos na parte inferior da estrutura dos dedos, os quais, ao serem ativados, realizam o movimento de flexão. O retorno de cada falange, ou seja, movimento de extensão dos dedos, ocorre de forma passiva. Foram instalados na parte superior das falanges elementos elásticos que são responsáveis por este movimento. Para monitorar os ângulos formados por cada falange foi utilizado um sensor do tipo resistivo que fica inserido dentro das falanges, variando sua resistência elétrica de acordo com a variação dos ângulos. Somado a este sistema, foi desenvolvido um controlador baseado em lógica fuzzy que se mostrou eficiente no monitoramento da posição dos dedos da mão robótica. Verificou-se que o desempenho da mão robótica pode ser considerado adequado, pois conseguiu atingir parcialmente os ângulos desejados de projeto.Este trabalho está fundamentado em estudos que comprovam o grande índice de rejeição por parte de pessoas amputadas ao utilizarem próteses de membros superiores devido a problemas diversos, tais como: peso, ruído elevado e falta de antropomorfismo. Nesse contexto, neste trabalho é apresentado o desenvolvimento de uma mão robótica cujo acionamento é realizado por atuadores não convencionais, constituídos de fios de uma Liga com Memória de Forma (LMF). A estrutura mecânica da mão robótica foi projetada em programa computacional CAD e posteriormente fabricada em polímero ABS por meio de prototipagem rápida usando uma impressora tridimensional. O projeto foi concebido parcialmente com base nas características fisiológicas da mão humana, no que diz respeito principalmente aos ângulos formados pelas falanges dos dedos. Foi desenvolvido um sistema mecânico para acondicionar os fios finos de uma LMF de Ni-Ti de forma compacta denominado neste trabalho por Músculo Artificial (MA) o que facilitou a compactação dos fios de LMF. A atuação dos dedos ocorre pela ativação dos MA que estão conectados a cabos dispostos na parte inferior da estrutura dos dedos, os quais, ao serem ativados, realizam o movimento de flexão. O retorno de cada falange, ou seja, movimento de extensão dos dedos, ocorre de forma passiva. Foram instalados na parte superior das falanges elementos elásticos que são responsáveis por este movimento. Para monitorar os ângulos formados por cada falange foi utilizado um sensor do tipo resistivo que fica inserido dentro das falanges, variando sua resistência elétrica de acordo com a variação dos ângulos. Somado a este sistema, foi desenvolvido um controlador baseado em lógica fuzzy que se mostrou eficiente no monitoramento da posição dos dedos da mão robótica. Verificou-se que o desempenho da mão robótica pode ser considerado adequado, pois conseguiu atingir parcialmente os ângulos desejados de projeto.

Nous nous intéressons à la conception des mains mécaniques anthropomorphes destinées à manipuler des objets dans un environnement humain. Via l'analyse du mouvement de sujets humains lors d'une tâche de manipulation de référence, nous proposons une méthode pour évaluer la capacité des mains robotiques à manipuler les objets. Nous montrons comment les rapports de couplage angulaires entre les articulations et les limites articulaires, influent sur l'aptitude à manipuler dynamiquement des objets. Nous montrons également l'impact du poignet sur les tâches de manipulation rapides. Nous proposons une stratégie pour calculer les forces de manipulation en bout de doigts et dimensionner les moteurs d'un tel préhenseur. La méthode proposée est dépendante de la tâche visée et s'adapte à tout type de mouvement dès lors qu'il peut être capturé et analysé. Dans une deuxième partie, consacrée aux robots manipulateurs, nous élaborons des algorithmes de commande optimale. En considérant l'énergie cinétique du robot comme une métrique, le modèle dynamique est formulé sous forme tensorielle dans le cadre de la géométrie Riemannienne. La discrétisation temporelle est basée sur les Éléments Finis d'Hermite. Nous intégrons les équations de Lagrange du mouvement par une méthode de perturbation. Des exemples de simulation illustrent la superconvergence de la technique d'Hermite. Le critère de contrôle est choisi indépendant des paramètres de configuration. Les équations de la commande associées aux équations du mouvement se révèlent covariantes. La méthode de commande optimale proposée consiste à minimiser la fonction objective correspondant au critère invariant sélectionné. / We focus on the design of anthropomorphous mechanical hands destined to manipulate objects in a human environment. Via the motion analysis of a reference manipulation task performed by human subjects, we propose a method to evaluate a robotic hand manipulation capacities. We demonstrate how the angular coupling between the fingers joints and the angular limits affect the hands potential to manipulate objects. We also show the influence of the wrist motions on the manipulation task. We propose a strategy to calculate the fingertip manipulation forces and dimension the fingers motors. In a second part devoted to articulated robots, we elaborate optimal control algorithms. Regarding the kinetic energy of the robot as a metric, the dynamic model is formulated tensorially in the framework of Riemannian geometry. The time discretization is based on the Hermite Finite Elements.A time integration algorithm is designed by implementing a perturbation method of the Lagrange's motion equations. Simulation examples illustrate the superconvergence of the Hermite's technique. The control criterion is selected to be coordinate free. The control equations associated with the motion equations reveal to be covariant. The suggested control method consists in minimizing the objective function corresponding to the selected invariant criterion.