Cable-actuated manipulators (or 'cable robots') constitute a relatively new classification of robots which use motors, located at fixed remote locations, to manipulate an end-effector by extending or retracting cables. These manipulators possess a number of unique properties which make them proficient with tasks involving high payloads, large workspaces, and dangerous or contaminated environments. However, a number of challenges exist which have limited the mainstream emergence of cable robots. This thesis addresses two of the most important of these issues-- workspace analysis and disturbance compensation. Workspace issues are particularly important, as many large-scale applications require the end-effector to operate in regions of a particular shape, and to exert certain minimum forces throughout those regions. The 'Force-Feasible Workspace' represents the set of end-effector positions, for a given robot design, for which the robot can exert a set of required forces on its environment. This can be considered as the robot's 'usable' workspace, and an analysis of this workspace shape for point-mass cable robots is therefore presented to facilitate optimal cable robot design. Numerical simulation results are also presented to validate the analytical results, and to aid visualization of certain complex workspace shapes. Some cable robot applications may require mounting motors to moving bases (i.e. mobile robots) or other surfaces which are subject to disturbances (i.e. helicopters or crane arms). Such disturbances can propagate to the end-effector and cause undesired motion, so the rejection of motor mount disturbances is also of interest. This thesis presents a strategy for measuring these disturbances and compensating for them. General approaches and implementation issues are explored qualitatively with a simple one-degree-of-freedom prototype (including a strategy for mitigating accelerometer drift), and quantitative simulation results are presented as a proof of concept.

Malgré le progrès de l'automatisation industrielle, les solutions robotiques ne sont pas encore couramment utilisées dans le secteur du génie civil. Plus spécifiquement, les tâches de ponçage, telles que le désamiantage, sont toujours effectuées par des opérateurs humains utilisant des outils électriques et hydrauliques classiques. Cependant, avec la diminution du coût relatif des machines par rapport au travail humain et les réglementations sanitaires strictes applicables à des travaux aussi risqués, les robots deviennent progressivement des alternatives crédibles pour automatiser ces tâches et remplacer les humains.Dans cette thèse, des nouvelles approches de contrôle de ponçage de surface sont élaborées. Le premier contrôleur est un contrôleur hybride position-force avec poignet conforme. Il est composé de 3 boucles de commande, force, position et admittance. La commutation entre les commandes pourrait créer des discontinuités, ce qui a été résolu en proposant une commande de transition. Dans ce contrôleur, la force de choc est réduite par la commande de transition proposée entre les modes espace libre et contact. Le second contrôleur est basé sur un modèle de ponçage développé et un contrôleur hybride adaptatif position-vitesse-force. Les contrôleurs sont validés expérimentalement sur un bras robotique à 7 degrés de liberté équipé d'une caméra et d'un capteur de force-couple. Les résultats expérimentaux montrent de bonnes performances et les contrôleurs sont prometteurs. De plus, une nouvelle approche pour contrôler la stabilité des manipulateurs mobiles en temps réel est présentée. Le contrôleur est basé sur le « zero moment point », il a été testé dans des simulations et il a été capable de maintenir activement la stabilité de basculement du manipulateur mobile tout en se déplaçant. En outre, les incertitudes liées à la modélisation et aux capteurs sont prises en compte dans les contrôleurs mentionnés où des observateurs sont proposés.Les détails du développement et de l'évaluation des différents contrôleurs proposés sont présentés, leurs mérites et leurs limites sont discutés et des travaux futurs sont suggérés. / Despite the advancements in industrial automation, robotic solutions are not yet commonly used in the civil engineering sector. More specifically, grinding tasks such as asbestos removal, are still performed by human operators using conventional electrical and hydraulic tools. However, with the decrease in the relative cost of machinery with respect to human labor and with the strict health regulations on such risky jobs, robots are progressively becoming credible alternatives to automate these tasks and replace humans.In this thesis, novel surface grinding control approaches are elaborated. The first controller is based on hybrid position-force controller with compliant wrist and a smooth switching strategy. In this controller, the impact force is reduced by the proposed smooth switching between free space and contact modes. The second controller is based on a developed grinding model and an adaptive hybrid position-velocity-force controller. The controllers are validated experimentally on a 7-degrees-of-freedom robotic arm equipped with a camera and a force-torque sensor. The experimental results show good performances and the controllers are promising. Additionally, a new approach for controlling the stability of mobile manipulators in real time is presented. The controller is based on zero moment point, it is tested in simulations and it was able to actively maintain the tip-over stability of the mobile manipulator while moving. Moreover, the modeling and sensors uncertainties are taken into account in the mentioned controllers where observers are proposed. The details of the development and evaluation of the several proposed controllers are presented, their merits and limitations are discussed and future works are suggested.

This project investigated the implementation and evaluation of various collision-free path planning algorithms for the Saab Seaeye eM1-7 6-DOF Electric Manipulator (eManip). The primary goal was to enhance the autonomous performance of the eManip by integrating efficient path planning methodologies, ultimately ensuring the avoidance of collisions and manipulator singularities during underwater operations. Key algorithms examined included the Rapidly-exploring Random Trees (RRT) algorithm and its enhanced variants. Through simulation tests in MATLAB and Gazebo, metrics such as planning time, path length, and the number of explored nodes were evaluated. The results highlighted the robustness of Goal-biased and Bidirectional RRT* (Gb-Bd-RRT*), which consistently performed well across various environments. The research also highlighted the correlation between algorithm effectiveness and specific task attributes, emphasizing their adaptability to complex environments. This research contributes valuable insights into the effectiveness of path planning algorithms, informing the selection and integration of viable strategies for 6-DOF robotic manipulators.