abstract: Myoelectric control is lled with potential to signicantly change human-robot interaction. Humans desire compliant robots to safely interact in dynamic environments associated with daily activities. As surface electromyography non-invasively measures limb motion intent and correlates with joint stiness during co-contractions, it has been identied as a candidate for naturally controlling such robots. However, state-of-the-art myoelectric interfaces have struggled to achieve both enhanced functionality and long-term reliability. As demands in myoelectric interfaces trend toward simultaneous and proportional control of compliant robots, robust processing of multi-muscle coordinations, or synergies, plays a larger role in the success of the control scheme. This dissertation presents a framework enhancing the utility of myoelectric interfaces by exploiting motor skill learning and exible muscle synergies for reliable long-term simultaneous and proportional control of multifunctional compliant robots. The interface is learned as a new motor skill specic to the controller, providing long-term performance enhancements without requiring any retraining or recalibration of the system. Moreover, the framework oers control of both motion and stiness simultaneously for intuitive and compliant human-robot interaction. The framework is validated through a series of experiments characterizing motor learning properties and demonstrating control capabilities not seen previously in the literature. The results validate the approach as a viable option to remove the trade-o between functionality and reliability that have hindered state-of-the-art myoelectric interfaces. Thus, this research contributes to the expansion and enhancement of myoelectric controlled applications beyond commonly perceived anthropomorphic and \intuitive control" constraints and into more advanced robotic systems designed for everyday tasks. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2015

La rigidité est un des objectifs de performance les plus importants pris en compte lors de la conception de systèmes robotiques. Le contrôle de la raideur physique en cours de tâche est une problématique scientifique en plein essor dans le cadre de la conception innovante de robots à forte polyvalence. L’association d’une structure robotique compliante et d’un composant en alliage à mémoire de forme (AMF) est réalisée dans le but d’obtenir des cartes de compliance variables dans le temps sur un même espace de travail. Les AMF sont en effet des matériaux actifs qui possèdent des caractéristiques comportementales pouvant être exploitées dans cette application. La structure considérée pour l’étude n’a pas de degré de liberté interne mais sa déformation permet de créer un pseudo-espace de travail. Celui-ci diffère selon l’état activé/non-activé de l’AMF. L’intersection des deux espaces obtenus représente alors les positions de l’effecteur où il est possible d’avoir des valeurs de compliance différentes. Les cartes obtenues montrent des caractéristiques intéressantes pour la perspective de la conception de robots polyvalents ayant une nouvelle forme de reconfigurabilité basée sur le changement de propriétés matérielles. / The rigidity is one of the most important performance targets which is taken into account for the design of robotic systems. The control of the physical stiffness during industrial tasks is a scientific issue which is rapidly expanding in the context of the innovative design of highly polyvalent robots. The combination of a compliant robotic structure and a shape memory alloy (SMA) component is carried out in the aim of obtaining variable compliance maps over time and in the same workspace. SMAs are actually active materials with specific thermomechanical properties which can be used in this application. The considered structure has no internal degree of freedom, but the deformation of the arms allows the creation of a “Pseudo-Workspace” (PWS). This PWS varies as a function of the activated/non-activated state of the SMA component. The intersection of the two obtained PWSs represents the effector’s positions where it is possible to have different compliance values. Generated maps show interesting characteristics in the perspective of the design of polyvalent robots based on a new type of reconfigurability (change of material properties).