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In this thesis, I present novel strategies for controlling objects with high degrees of freedom for the purpose of robotic control and computer animation, including articulated objects such as human bodies or robots and deformable objects such as ropes and cloth. Such control is required for common daily movements such as folding arms, tying ropes, wrapping objects and putting on clothes. Although there is demand in computer graphics and animation for generating such scenes, little work has targeted these problems. The difficulty of solving such problems are due to the following two factors: (1) The complexity of the planning algorithms: The computational costs of the methods that are currently available increase exponentially with respect to the degrees of freedom of the objects and therefore they cannot be applied for full human body structures, ropes and clothes . (2) Lack of abstract descriptors for complex tasks. Models for quantitatively describing the progress of tasks such as wrapping and knotting are absent for animation generation. In this work, we employ the concept of a task-centric manifold to quantitatively describe complex tasks, and incorporate a bi-mapping scheme to bridge this manifold and the configuration space of the controlled objects, called an object-centric manifold. The control problem is solved by first projecting the controlled object onto the task-centric manifold, then getting the next ideal state of the scenario by local planning, and finally projecting the state back to the object-centric manifold to get the desirable state of the controlled object. Using this scheme, complex movements that previously required global path planning can be synthesised by local path planning. Under this framework, we show the applications in various fields. An interpolation algorithm for arbitrary postures of human character is first proposed. Second, a control scheme is suggested in generating Furoshiki wraps with different styles. Finally, new models and planning methods are given for quantitatively control for wrapping/ unwrapping and dressing/undressing problems.

A robótica móvel é uma área de pesquisa que está obtendo grande atenção da comunidade científica. O desenvolvimento de robôs móveis autônomos, que sejam capazes de interagir com o ambiente, aprender e tomar decisões corretas para que suas tarefas sejam executadas com êxito é o maior desafio em robótica móvel. O desenvolvimento destes sistemas inteligentes e autônomos consiste em uma área de pesquisa multidisciplinar considerada recente e extremamente promissora que envolve; por exemplo, inteligência artificial, aprendizado de máquina, estimação estatística e sistemas embarcados. Dentro desse contexto, esse trabalho aborda o problema de navegação e monitoramento de ambientes utilizando robôs móveis. Dada uma representação do ambiente (mapa topológico) e uma lista com urgências de cada uma das regiões do mapa, o robô deve estimar qual o percurso mais eficiente para monitorar esse ambiente. Uma vez que a urgência de cada região não visitada aumenta com o tempo, o trajeto do robô deve se adaptar a essas alterações. Entre as diversas aplicações práticas desse tipo de algoritmo, destaca-se o desenvolvimento de sistemas de segurança móveis inteligentes / The mobile robotics is a research area that has started to get some serious attention from the scientific community. The development of robots able to interact with the environment - to learn and make correct decisions so their tasks are successfully completed - is the biggest challenge in mobile robotics. The development of these intelligent and autonomous systems consists of a multidisciplinary research area considered recent and very promising that involves, for example, artificial intelligence, machine learning, statistical estimation and embedded systems. Within this context, this paper addresses the problem of navigation in dynamic environments with priorities using mobile robots. Given a representation of the environment (topological map) and a list of priorities for each region of the map, the robot must estimate what is the most efficient way to monitor this environment. As the dynamic priority of each region increases with time since the last visit of the robot, its trajectory must adapt to these changes. This approach is similar to the traveling salesman, but a solution that specifically addresses the problem described in this dissertation was not found in the literature. Among the many practical applications of this type of algorithm, we highlight the development of smart mobile security systems

This thesis concerns the design, construction, control, and testing of soft robotic actuators to be used in a soft robotic exoskeleton; the Boa Exoskeleton could be used for joint rehabilitation including: wrist, elbow and possibly shoulder or any joint that requires a soft body actuator to aid with bending movement. We detail the design, modeling and fabrication of two types of actuators: Fiber-reinforced Actuator and PneuNet Actuator. Fiber-Reinforced actuator was chosen for the exoskeleton due to its higher force. The Fiber-Reinforced actuator molds were 3D printed, four models were made. Two materials were used to fabricate the models: Dragon Skin 30A and Sort-A-Clear 40A. Two number of windings: (n=40) and (n=25), actuators wrapped with carbon fiber. An air tank was used to supply pressure. The actuators were studied at different pressures. Pressure-force relation was studied, and a close to linear relationship was found. Boa Exoskeleton was made for wrist. Electromyography (EMG) was used; Four EMG receptors were put around the arm. EMG was utilized to actuate the Boa Exoskeleton and record the muscle movement. Five tests were done on six human subjects to validate the Boa Exoskeleton. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection