Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references. Also available in electronic version. Access restricted to campus users.

Screens mediate an ever-increasing part of our experience today. While the space within our screens is indispensable - as perceptually ‘real’ as embodied experience itself - this space tends to exclude the hands and body in favour of the eye and mind. This bifurcation does not recognize or allow for the integration of body and mind that is both fundamental to our well-being and vital to the process of making things. Moreover, immersion within our screens dulls an awareness of ourselves in relation to them. This thesis is an exploration of the immense potential that resides in the space between our hands and screens. Through a series of themed meditations and experimental set-ups, my research aims to prove that reconciliation between digital and embodied mediation can simultaneously offer enchantment to both our bodies and our minds, and furthermore, that the empowered hand is essential for the maturation of digital technologies.

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The problem considered in this thesis is developing a set of digital features relevant in describing finger-hand function of early-onset rheumatoid arthritis (RA) patients. The premise is based on a novel telerehabilitation gaming system that operates on a store-and-forward design. The solution to this problem was to develop a full-scale gaming platform to examine client movement performance for precision aiming tasks based on a set of digital features. To complement the movement performance, still imagery in three unique poses are captured during a session to detect visual symptoms during disease activity and early warning signs of deformities that can arise from joint damage. Resulting data is gathered in a clinic or housed in a content management system where features are extracted and analyzed, providing reports/queries for care providers and allowing remote monitoring. The goal is to help automate monitoring patient finger-hand function between office visits from a remote location, on a smaller scale and with minimal supervision. The contributions presented in this work include development of a detailed set of digital features derived from a custom built gaming platform to highlight client movement performance and algorithms to extract hand structure to approximate goniometry measurements of joint angles monitoring for potential changes during progression of the disease. The significance of this contribution is that it provides a readily accessible, experimental platform for the provision of physical therapy tailored to the individual RA patient through the use of a telerehabilitation gaming platform.

Thesis (M.E.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (leaves 99-101). Also available via the World Wide Web.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 112-121). Also available in electronic version.

You can only perceive the location of a touch when you know where your hands are in space. Locating a touch to the body requires the integration of internal (somatotopic) and external (spatial) reference frames. In order to explore the relative contribution of internal versus external information, this thesis employed a crossed-hands tactile temporal order judgment (TOJ) task. This task requires participants to indicate which of two vibrations, one to each hand, occurred first. The magnitude of the deficit observed when the hands are crossed over the midline provides an index into how internal and external reference frames are integrated. This thesis first showed that the crossed-hands tactile TOJ task is a reliable measure, supporting its use as a measure of reference frame integration. Next, this thesis applied a probabilistic model to theoretically estimate the weights placed on the internal and external reference frames. We showed that a bias towards external information results in a larger external weight and vice versa for internal information. Finally, using the model we showed that the crossed-hands deficit is reduced while lying down, supporting an influence of vestibular information on the external reference frame. Taken together, this thesis highlights that we are able to flexibly adapt the weighting of different spatial representations of touch. / Thesis / Doctor of Science (PhD) / Determining the boundary of our body requires we localize the touches to our body. When the body moves and interacts with the world this determination becomes more difficult. Integrating information from other senses can support the localization of touch, and thus knowledge of our body. For example, to locate a touch to your right hand, you must feel the touch on your right hand, but also determine where your right hand is located in space. This thesis shows that the contributions of each sense to locate a touch is consistent within an individual and remains consistent over time. Interestingly, based on the availability of each sense, we flexibly adapt their contributions to ensure that our ability to locate the touch remains unchanged. What we define as our body is constructed based on the information available in the present moment.

La prensión y manipulación de objetos se ha convertido en un área de gran interés en robótica, especialmente debido al desarrollo de dispositivos de prensión diestra como las manos antropomórficas, que incrementan la flexibilidad y verstilidad de los brazos robóticos, permitiendo así la prensión y manipulación de una gran variedad de objetos con un solo efector final. Esta tesis aborda varios problemas de planificación asociados a la prensión y manipulación de objetos discretos arbitrarios, esto es, objetos de forma arbitraria descritos mediante nubes de puntos o mallas poligonales. La obtención de una prensión con clausura de fuerza (force-closure) y de una prensión localmente óptima se realiza mediante procedimientos de búsqueda orientada basados en razonamientos geométricos en el espacio de prensiones. La medida de calidad de prensión utilizada es la mayor fuerza generalizada de perturbación que la prensión puede resistir, independientemente de la dirección de la perturbación. Sin embargo, las manos mecánicas y dispositivos de prensión reales difícilmente pueden asegurar que los dedos toquen el objeto justamente en los puntos de contacto calculados. Las regiones de contacto independiente (ICRs) se definen de forma tal que un dedo colocado en cada ICR asegura una prensión con clausura de fuerza; estas regiones otorgan robustez frente a errores en el posicionamiento de los dedos. Esta tesis presenta un algoritmo para obtener las ICRs con cualquier número de contactos con o sin fricción sobre la superficie de cualquier objeto tridimensional, asegurando también una calidad mínima controlada. La aproximación planteada genera las ICRs creciéndolas alrededor de los puntos de contacto de una prensión inicial apropiada, por ejemplo una prensión localmente óptima. Este método se extiende también para el cálculo de ICRs cuando varios contactos están fijados de antemano. El concepto de regiones de no prensión (NGRs) se introduce en este trabajo. Las NGRs se definen de forma tal que un dedo colocado en cada NGR siempre produce una prensión sin clausura de fuerza, independientemente de la posición exacta de cada dedo. Las ICRs y NGRs se utilizan para explorar de forma eficiente el espacio de prensiones. Este espacio es construido mediante un método de muestreo que provee muestras de prensiones con o sin clausura de fuerza, que luego se utilizan para calcular ICRs o NGRs respectivamente, y que luego sirven para etiquetar las configuraciones del espacio de prensiones. Se presenta también una secuencia de muestreo determinístico que permite una exploración incremental y uniforme del espacio de prensiones. La generación del espacio de prensiones se utiliza posteriormente para resolver el problema de reprensión (regrasping), esto es, la obtención de trayectorias de las puntas de los dedos sobre la superficie del objeto para cambiar de una prensión inicial a una final sin perder la condición de la clausura de fuerza. La tesis incluye ejemplos de aplicación para ilustrar el desempeño y la relevancia de los algoritmos planteados. / Object grasping and manipulation has become an area of great interest in robotics, specially due to the development of dexterous grasping devices like anthropomorphic hands that increase the flexibility and versatility of the robot arms, allowing the grasping and manipulation of a large variety of objects with a single end effector. This thesis tackles several planning problems associated with grasping and manipulation of arbitrary discrete objects, i.e. objects described with a cloud of points or a polygonal mesh. The computation of a force closure grasp and a locally optimal grasp is tackled using oriented search procedures based on geometric reasoning in the wrench space. The grasp quality measure considered is the largest perturbation wrench that the grasp can resist independently of the perturbation direction. However, real mechanical hands and grasping devices can hardly assure that the fingers will precisely touch the object at the computed contact points. Independent contact regions (ICRs) such that a finger contact in each ICR ensures a force closure grasp, provide robustness in front of finger positioning errors. This thesis presents an approach to compute ICRs with any number of frictionless or frictional contacts on the surface of any 3D object, assuring a controlled minimum grasp quality. The approach generates the ICRs by growing them around the contact points of a given appropriated starting grasp, like for instance a locally optimal grasp. The approach is also extended to compute the ICRs when several contacts are fixed beforehand. The notion of Non-Graspable Regions (NGRs) is introduced in this work, such that a finger contact in each NGR always produces a non-force closure grasp independently of the exact position of each finger. The ICRs and NGRs are used to efficiently explore the grasp space. The grasp space is constructed using a sampling method that provides samples of force closure or non force closure grasps used to compute ICRs or NGRs, respectively, which are used to label the configurations of the grasp space. An efficient deterministic sampling sequence is provided to allow a good incremental and uniform exploration of the grasp space. The generation of the grasp space is then applied to solve the regrasping problem, i.e. to obtain trajectories of the fingertips on the object surface in order to change from an initial to a final grasp without losing the force closure condition. Application examples are included to illustrate the relevance and performance of the proposed approaches.

by Lo, Ka-wah. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 76-81 (2nd gp.)). / Acknowledgments --- p.i / Abstract --- p.ii / Notations --- p.iii / List of Figures --- p.v / List of Tables --- p.vii / Chapter 1. --- Introduction / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Literature Review --- p.4 / Chapter 1.3 --- Objective --- p.10 / Chapter 2. --- Comparison of Different Approaches / Chapter 2.1 --- Sample Manipulator --- p.11 / Chapter 2.1.1 --- Force Decomposition Method --- p.12 / Chapter 2.1.2 --- Forward Rate Kinematics Base Method --- p.15 / Chapter 2.1.3 --- Grassmann Geometry Method --- p.18 / Chapter 2.2 --- Comparison Criteria --- p.20 / Chapter 2.2.1 --- Computational Complexity --- p.20 / Chapter 2.2.2 --- Scope of Application --- p.22 / Chapter 2.3 --- Summary --- p.23 / Chapter 3. --- Enumeration of Configuration Singularity / Chapter 3.1 --- Novel 6 DOF --- p.25 / Chapter 3.1.1 --- Result Analysis --- p.31 / Chapter 3.2 --- A 3 DOF with Symmetric Base --- p.33 / Chapter 3.2.1 --- Result Analysis --- p.35 / Chapter 3.3 --- A 3 DOF with Non-Symmetric Base --- p.36 / Chapter 3.3.1 --- Result Analysis --- p.37 / Chapter 3.4 --- A New Model of 6-SPS Defined by Kong et al --- p.40 / Chapter 3.5 --- A New Class of 6-SPS Platform-Type Parallel Manipulator --- p.45 / Chapter 3.5.1 --- The Hexagonal Base --- p.46 / Chapter 3.5.2 --- The Pentagonal Base --- p.50 / Chapter 3.5.3 --- The Tetragonal Base --- p.52 / Chapter 3.5.4 --- The Triangular Base --- p.55 / Chapter 3.6 --- Summary --- p.59 / Chapter 4. --- Numerical Analysis / Chapter 4.1 --- Parameter Analysis --- p.60 / Chapter 4.1.1 --- One Unknown Variable --- p.61 / Chapter 4.1.2 --- Two Unknown Variables --- p.63 / Chapter 4.2 --- Critical Value of Ratio R/q --- p.69 / Chapter 4.3 --- Summary --- p.72 / Chapter 5. --- Conclusions and Future Work / Chapter 5.1 --- Conclusions --- p.73 / Chapter 5.2 --- Future Work --- p.75 / References --- p.76 / Appendix --- p.82

Fok Lo Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 133-135). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Multi-fingered Robotic Hands --- p.1 / Chapter 1.2 --- Grasping Force Optimization --- p.2 / Chapter 1.3 --- Neural Networks --- p.6 / Chapter 1.4 --- Previous Work for Grasping Force Optimization --- p.9 / Chapter 1.5 --- Contributions of this work --- p.10 / Chapter 1.6 --- Organization of this thesis --- p.12 / Chapter 2. --- Problem Formulations --- p.13 / Chapter 2.1 --- Grasping Force Optimization without Joint Torque Limits --- p.14 / Chapter 2.1.1 --- Linearized Friction Cone Approach --- p.15 / Chapter i. --- Linear Formulation --- p.17 / Chapter ii. --- Quadratic Formulation --- p.18 / Chapter 2.1.2 --- Nonlinear Friction Cone as Positive Semidefinite Matrix --- p.19 / Chapter 2.1.3 --- Constrained Optimization with Nonlinear Inequality Constraint --- p.20 / Chapter 2.2 --- Grasping Force Optimization with Joint Torque Limits --- p.21 / Chapter 2.2.1 --- Linearized Friction Cone Approach --- p.23 / Chapter 2.2.2 --- Constrained Optimization with Nonlinear Inequality Constraint --- p.23 / Chapter 2.3 --- Grasping Force Optimization with Time-varying External Wrench --- p.24 / Chapter 2.3.1 --- Linearized Friction Cone Approach --- p.25 / Chapter 2.3.2 --- Nonlinear Friction Cone as Positive Semidefinite Matrix --- p.25 / Chapter 2.3.3 --- Constrained Optimization with Nonlinear Inequality Constraint --- p.26 / Chapter 3. --- Recurrent Neural Network Models --- p.27 / Chapter 3.1 --- Networks for Grasping Force Optimization without Joint Torque Limits / Chapter 3.1.1 --- The Primal-dual Network for Linear Programming --- p.29 / Chapter 3.1.2 --- The Deterministic Annealing Network for Linear Programming --- p.32 / Chapter 3.1.3 --- The Primal-dual Network for Quadratic Programming --- p.34 / Chapter 3.1.4 --- The Dual Network --- p.35 / Chapter 3.1.5 --- The Deterministic Annealing Network --- p.39 / Chapter 3.1.6 --- The Novel Network --- p.41 / Chapter 3.2 --- Networks for Grasping Force Optimization with Joint Torque Limits / Chapter 3.2.1 --- The Dual Network --- p.43 / Chapter 3.2.2 --- The Novel Network --- p.45 / Chapter 3.3 --- Networks for Grasping Force Optimization with Time-varying External Wrench / Chapter 3.3.1 --- The Primal-dual Network for Quadratic Programming --- p.48 / Chapter 3.3.2 --- The Deterministic Annealing Network --- p.50 / Chapter 3.3.3 --- The Novel Network --- p.52 / Chapter 4. --- Simulation Results --- p.54 / Chapter 4.1 --- Three-finger Grasping Example of Grasping Force Optimization without Joint Torque Limits --- p.54 / Chapter 4.1.1 --- The Primal-dual Network for Linear Programming --- p.57 / Chapter 4.1.2 --- The Deterministic Annealing Network for Linear Programming --- p.59 / Chapter 4.1.3 --- The Primal-dual Network for Quadratic Programming --- p.61 / Chapter 4.1.4 --- The Dual Network --- p.63 / Chapter 4.1.5 --- The Deterministic Annealing Network --- p.65 / Chapter 4.1.6 --- The Novel Network --- p.57 / Chapter 4.1.7 --- Network Complexity Analysis --- p.59 / Chapter 4.2 --- Four-finger Grasping Example of Grasping Force Optimization without Joint Torque Limits --- p.73 / Chapter 4.2.1 --- The Primal-dual Network for Linear Programming --- p.75 / Chapter 4.2.2 --- The Deterministic Annealing Network for Linear Programming --- p.77 / Chapter 4.2.3 --- The Primal-dual Network for Quadratic Programming --- p.79 / Chapter 4.2.4 --- The Dual Network --- p.81 / Chapter 4.2.5 --- The Deterministic Annealing Network --- p.83 / Chapter 4.2.6 --- The Novel Network --- p.85 / Chapter 4.2.7 --- Network Complexity Analysis --- p.87 / Chapter 4.3 --- Three-finger Grasping Example of Grasping Force Optimization with Joint Torque Limits --- p.90 / Chapter 4.3.1 --- The Dual Network --- p.93 / Chapter 4.3.2 --- The Novel Network --- p.95 / Chapter 4.3.3 --- Network Complexity Analysis --- p.97 / Chapter 4.4 --- Three-finger Grasping Example of Grasping Force Optimization with Time-varying External Wrench --- p.99 / Chapter 4.4.1 --- The Primal-dual Network for Quadratic Programming --- p.101 / Chapter 4.4.2 --- The Deterministic Annealing Network --- p.103 / Chapter 4.4.3 --- The Novel Network --- p.105 / Chapter 4.4.4 --- Network Complexity Analysis --- p.107 / Chapter 4.5 --- Four-finger Grasping Example of Grasping Force Optimization with Time-varying External Wrench --- p.109 / Chapter 4.5.1 --- The Primal-dual Network for Quadratic Programming --- p.111 / Chapter 4.5.2 --- The Deterministic Annealing Network --- p.113 / Chapter 4.5.3 --- The Novel Network --- p.115 / Chapter 5.5.4 --- Network Complexity Analysis --- p.117 / Chapter 4.6 --- Four-finger Grasping Example of Grasping Force Optimization with Nonlinear Velocity Variation --- p.119 / Chapter 4.5.1 --- The Primal-dual Network for Quadratic Programming --- p.121 / Chapter 4.5.2 --- The Deterministic Annealing Network --- p.123 / Chapter 4.5.3 --- The Novel Network --- p.125 / Chapter 5.5.4 --- Network Complexity Analysis --- p.127 / Chapter 5. --- Conclusions and Future Work --- p.129 / Publications --- p.132 / Bibliography --- p.133 / Appendix --- p.136