<p>This thesis investigates two significant problems in control and coordination of complex teleoperation systems as they relate to the operation of a mobile robotic manipulator. The first part of the thesis focuses on the design of a control framework to resolve kinematic redundancy in teleoperation of a mobile robotic manipulator. Apart from the redundancy, workspace considerations for the operator and robot and asymmetry of master and slave systems pose significant design challenges in such telerobotic systems . The second part of the thesis considers psychophysical aspects of teleoperation from the operator's perspective. This part presents a method for automatic {\em optimal} positioning of a single camera for a remotely navigated mobile robot in systems with a controllable camera platform. In each part, a constrained optimization problem is formulated and solved in real time. The solution of these optimization problems are integrated seamlessly into the teleoperation control framework in order to assist the operator in accomplishing the main task. The proposed control framework in the first part allows the operator to concentrate on the manipulation task while the mobile base and arm joint configurations are automatically {\em optimized} according to the needs of the task. Autonomous control subtasks are defined to guide the base and the arms towards this optimal configuration while the operator teleoperates the end-effector(s) of the mobile arm(s). The teleoperation and autonomous control tasks have adjustable relative priorities set by the system designer. The work in the second part enables the operator to focus mainly on navigation and manipulation while the camera viewpoint is automatically adjusted. The workspace and motion limits of the camera system and the location of the obstacles are taken into consideration in camera view planning. A head tracking system enables the operator to use his/her head movements as an extra control input to guide the camera placement, if and when necessary. Both proposed controllers have been implemented and evaluated in teleoperation experiments and user studies. The results of these experiments confirm the effectiveness of these controllers and demonstrate significant improvements compared to other existing controllers from the literature included in the studies.</p> / Master of Applied Science (MASc)

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Cette thèse se situe dans la planification et le suivi de mouvement d’un humanoïde mobile à deux bras. Premièrement, MDH est utilisé pour la modélisation cinématique. Afin de surmonter les insuffisances de la méthode d’Euler-Lagrange qui nécessitent des calculs d’énergie et ses dérivées partielles, la méthode de Kane est utilisée. En plus, la stabilité physique est analysée et un contrôleur est conçu. Deuxièmement, un algorithme avancée MaxiMin NSGA-II est proposée pour concevoir l’orientation et la position optimales de la plate-forme mobile (PB) et la configuration optimale du manipulateur supérieur (MS) étant donnée uniquement la pose initiale et les positions et orientations souhaitées des EEs. Un algorithme à connexion directe combinant BiRRT et la gradient-descente est conçu pour réaliser la transition de la pose initiale à la pose optimale, et une méthode d'optimisation géométrique est conçue pour optimiser et cohérer le chemin. En outre, les motions en avant sont obtenues en attribuant des orientations pour MB indiquant ainsi l'intention du robot. Afin de résoudre le problème d'échec de l’algorithme hors ligne, un algorithme en ligne est proposé en estimant les motions des obstacles dynamiques. De plus, afin d'optimiser les via-poses, un algorithme basé sur les via-points des EEs et MOGA est proposé en optimisant quatre fonctions objectives. Enfin, le problème de suivi de motion est étudié étant donné les motions des EEs dans l'espace de tâche. Au lieu de contrôler la motion absolue, deux motions relatives sont introduites pour réaliser la coordination et la coopération entre MB et MS. De plus, une technique mWLN est proposée pour éviter les limites des joints. / This thesis focuses on the motion planning and tracking of a dual-arm mobile humanoid. First, MDH is used for kinematic modeling. The co-simulation via Simulink-Adams on prototype is realized to validate the effectiveness of RBFNN controller. In order to overcome the shortcomings of Euler-Lagrange’s formulations that require calculating energy and energy derivatives, Kane’s method is used. In addition, physical stability is analyzed based on Kane’s method and a controller is designed using back-stepping technique. Secondly, an improved MaxiMin NSGA-II is proposed to design the mobile base’s (MB) optimal position-orientation and the upper manipulator’s (UM) optimal configuration given only the initial pose and end-effectors’ (EEs) desired positions-orientations. A direct connect algorithm combining BiRRT and gradient-descent is designed to plan the transition from initial pose to optimal pose, and a geometric optimization method is designed to optimize and cohere the path. In addition, forward motions are obtained by assigning orientations for MB thus indicating robot’s intention. In order to solve the failure problem of offline algorithm, an online algorithm is proposed while estimating dynamic obstacles’ motions. In addition, in order to optimize via-poses, an algorithm based on EEs’ via-points and MOGA is proposed by optimizing four via-pose-based objective functions. Finally, the motion tracking problem is studied given EEs’ motions in the task space. Instead of controlling the absolute motion, two relative motions are introduced to realize the coordination and cooperation between MB and UM. In addition, an modulated WLN technique is proposed to avoid joints’ limits.