Typescript. Includes bibliographical references (leaves 91-95).

My work revolves around Alexander Yakovlev’s vocal method which originates in the tradition of organic singing established in Russia by Glinka in the mid nineteenth century, and developed by the legendary Russian bass Fyodor Chalyapin. My approach to piano technique and performance formed as a direct result of Yakovlev’s principles and his vocal method, serves as the origin in my search for piano mastery. Being taught organic singing simultaneously with my piano studies by Yakovlev’s successor Natalia Pirozerskaya in my early childhood, I did not at that point see the full benefit of this approach for my piano skills. It was only after twelve years of trial and error in seeking to realise my inner expressive and virtuoso potential at the piano, that I understood the infinite value of Pirozerskaya’s teaching method and began to analyse the effect of organic singing on my pianistic process. Pirozerskaya grounds her research on the singing voice following Yakovlev’s concept of the vocal apparatus functioning as a sensory organ in relation to musical performance. Yakovlev developed a theory around this phenomenon which he labelled funzione d’attacco. This way, the singer’s inner artistic impulses cause a direct, natural motor response in his/her vocal organ, forming optimal corresponding movements which with training become automatic, almost reflexive. Pirozerskaya believes that because the vocal organ is an embodied instrument positioned close to the brain, organic vocal movements easily stimulate the brain, serving to alert and coordinate the motor-muscular responses of the entire body, and thus helping to form differentiated musical movements of the hands – the apparatus of the pianist. My research is focused on these phenomena in relation to piano playing. I am working towards systematising Pirozerskaya’s and my own further discoveries on how this unique vocalpiano method impacts on piano technique. Aiming to distinguish between the notions of a ‘good piano player’ and a ‘performing artist’, I am developing my proposed piano method of re-connecting the pianist with his inner artistic self. Combining my experience with relevant ideas of several renowned piano pedagogues from Frederick Chopin to the present, I propose an approach to piano playing which, I believe, has the capacity of maximising artistic expression in performance through developing a natural functional balance of pianistic movements inseparable from the pianist’s artistic aims

Thesis (Ph. D.)--University of Notre Dame, 2008. / Thesis directed by Maxwell E. Johnson for the Department of Theology. "April 2008." Includes bibliographical references (leaves 405-428).

Despite decades of research robotic manipulation systems outside of highly-structured industrial applications are still far from ubiquitous. Perhaps particularly curious is the fact that there appears to be a large divide between the theoretical grasp modeling literature and the practical manipulation community. Specifically, it appears that the most successful approaches to tasks such as pick-and-place or grasping in clutter are those that have opted for simple grippers or even suction systems instead of dexterous multi-fingered platforms. We argue that the reason for the success of these simple manipulation systemsis what we call passive stability: passive phenomena due to nonbackdrivable joints or underactuation allow for robust grasping without complex sensor feedback or controller design. While these effects are being leveraged to great effect, it appears the practical manipulation community lacks the tools to analyze them. In fact, we argue that the traditional grasp modeling theory assumes a complexity that most robotic hands do not possess and is therefore of limited applicability to the robotic hands commonly used today. We discuss these limitations of the existing grasp modeling literature and setout to develop our own tools for the analysis of passive effects in robotic grasping. We show that problems of this kind are difficult to solve due to the non-convexity of the Maximum Dissipation Principle (MDP), which is part of the Coulomb friction law. We show that for planar grasps the MDP can be decomposed into a number of piecewise convex problems, which can be solved for efficiently. Despite decades of research robotic manipulation systems outside of highlystructured industrial applications are still far from ubiquitous. Perhaps particularly curious is the fact that there appears to be a large divide between the theoretical grasp modeling literature and the practical manipulation community. Specifically, it appears that the most successful approaches to tasks such as pick-and-place or grasping in clutter are those that have opted for simple grippers or even suction systems instead of dexterous multi-fingered platforms. We argue that the reason for the success of these simple manipulation systemsis what we call passive stability: passive phenomena due to nonbackdrivable joints or underactuation allow for robust grasping without complex sensor feedback or controller design. While these effects are being leveraged to great effect, it appears the practical manipulation community lacks the tools to analyze them. In fact, we argue that the traditional grasp modeling theory assumes a complexity that most robotic hands do not possess and is therefore of limited applicability to the robotic hands commonly used today. We discuss these limitations of the existing grasp modeling literature and setout to develop our own tools for the analysis of passive effects in robotic grasping. We show that problems of this kind are difficult to solve due to the non-convexity of the Maximum Dissipation Principle (MDP), which is part of the Coulomb friction law. We show that for planar grasps the MDP can be decomposed into a number of piecewise convex problems, which can be solved for efficiently. We show that the number of these piecewise convex problems is quadratic in the number of contacts and develop a polynomial time algorithm for their enumeration. Thus, we present the first polynomial runtime algorithm for the determination of passive stability of planar grasps. For the spacial case we present the first grasp model that captures passive effects due to nonbackdrivable actuators and underactuation. Formulating the grasp model as a Mixed Integer Program we illustrate that a consequence of omitting the maximum dissipation principle from this formulation is the introduction of solutions that violate energy conservation laws and are thus unphysical. We propose a physically motivated iterative scheme to mitigate this effect and thus provide the first algorithm that allows for the determination of passive stability for spacial grasps with both fully actuated and underactuated robotic hands. We verify the accuracy of our predictions with experimental data and illustrate practical applications of our algorithm. We build upon this work and describe a convex relaxation of the Coulombfriction law and a successive hierarchical tightening approach that allows us to find solutions to the exact problem including the maximum dissipation principle. It is the first grasp stability method that allows for the efficient solution of the passive stability problem to arbitrary accuracy. The generality of our grasp model allows us to solve a wide variety of problems such as the computation of optimal actuator commands. This makes our framework a valuable tool for practical manipulation applications. Our work is relevant beyond robotic manipulation as it applies to the stability of any assembly of rigid bodies with frictional contacts, unilateral constraints and externally applied wrenches. Finally, we argue that with the advent of data-driven methods as well as theemergence of a new generation of highly sensorized hands there are opportunities for the application of the traditional grasp modeling theory to fields such as robotic in-hand manipulation through model-free reinforcement learning. We present a method that applies traditional grasp models to maintain quasi-static stability throughout a nominally model-free reinforcement learning task. We suggest that such methods can potentially reduce the sample complexity of reinforcement learning for in-hand manipulation.We show that the number of these piecewise convex problems is quadratic in the number of contacts and develop a polynomial time algorithm for their enumeration. Thus, we present the first polynomial runtime algorithm for the determination of passive stability of planar grasps.

No description available.

by Lam Miu-Ling. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 64-67). / Abstracts in English and Chinese. / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Mathematical Preliminaries and Problem Definition --- p.6 / Chapter 2.1 --- Grasp Synthesis in Discrete Domain / Chapter 2.2 --- Assumptions / Chapter 2.3 --- Frictionless Form-Closure Grasp / Chapter 2.4 --- Frictional Form-Closure Grasp / Chapter 2.5 --- Problem Definition / Chapter Chapter 3. --- A Qualitative Test Algorithm and a Local Search Algorithm --- p.18 / Chapter 3.1 --- A Qualitative Test Algorithm / Chapter 3.2 --- A Local Search Algorithm / Chapter 3.3 --- Grasp Planning under Kinematic Constraints / Chapter Chapter 4. --- A Divide-and-Conquer Technique --- p.29 / Chapter 4.1. --- Determining a Separating Hyperplane / Chapter 4.2. --- Divide-and-Conquer in Frictionless Case / Chapter 4.3. --- Divide-and-Conquer in Frictional Case / Chapter Chapter 5. --- Implementation and Examples --- p.40 / Chapter 6.1. --- Examples of Frictionless Grasps / Chapter 6.2. --- Examples of Frictional Grasps / Chapter 6.3. --- Examples of Grasps under Kinematic Constraints / Chapter Chapter 6. --- Conclusions --- p.62 / Bibliography --- p.64

The game of Cribbage has a complex way of counting points in the hands that are dealt to each player. Each player has a choice of what cards to keep and what cards to throw into an extra hand, called the crib, that one of the players gets to count towards his score. Ideally, you could try to keep the most points possible in your hand and your crib, or, conversely, the most points in your hand with the fewest points in your opponent’s crib. To add to the fun, a final card is randomly chosen that all three hands share. This thesis deals with finding optimal expected values for each player’s hand and the crib. Unfortunately, finding the exact optimal values is very difficult. However, I have managed to get bounds on the optimal values.

The Workshop for the Design and Control of Dexterous Hands was held at the MIT Artificial Intelligence Laboratory on November 5-6, 1981. Outside experts were brought together to discuss four topics: kinematics of hands, actuation and materials, touch sensing and control. This report summarizes the discussions of the participants and attempts to identify a consensus on applications, mechanical design, and control.

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.

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