A graph-theory-based C-space path planner for mobile robotic manipulators in close-proximity environments

In this thesis a novel guidance method for a 3-degree-of-freedom robotic manipulator arm in 3 dimensions for Improvised Explosive Device (IED) disposal has been developed. The work carried out in this thesis combines existing methods to develop a technique that delivers advantages taken from several other guidance techniques. These features are necessary for the IED disposal application. The work carried out in this thesis includes kinematic and dynamic modelling of robotic manipulators, T-space to C-space conversion, and path generation using Graph Theory to produce a guidance technique which can plan a safe path through a complex unknown environment. The method improves upon advantages given by other techniques in that it produces a suitable path in 3-dimensions in close-proximity environments in real time with no a priori knowledge of the environment, a necessary precursor to the application of this technique to IED disposal missions. To solve the problem of path planning, the thesis derives the kinematics and dynamics of a robotic arm in order to convert the Euclidean coordinates of measured environment data into C-space. Each dimension in C-space is one control input of the arm. The Euclidean start and end locations of the manipulator end effector are translated into C-space. A three-dimensional path is generated between them using Dijkstra’s Algorithm. The technique allows for a single path to be generated to guide the entire arm through the environment, rather than multiple paths to guide each component through the environment. The robotic arm parameters are modelled as a quasi-linear parameter varying system. As such it requires gain scheduling control, thus allowing compensation of the non-linearities in the system. A Genetic Algorithm is applied to tune a set of PID controllers for the dynamic model of the manipulator arm so that the generated path can then be followed using a conventional path-following algorithm. The technique proposed in this thesis is validated using numerical simulations in order to determine its advantages and limitations

Proceedings of the Thirteenth International Conference on Time-Resolved Vibrational Spectroscopy

The thirteenth meeting in a long-standing series of “Time-Resolved Vibrational Spectroscopy” (TRVS) conferences was held May 19th to 25th at the Kardinal Döpfner Haus in Freising, Germany, organized by the two Munich Universities - Ludwig-Maximilians-Universität and Technische Universität München. This international conference continues the illustrious tradition of the original in 1982, which took place in Lake Placid, NY. The series of meetings was initiated by leading, world-renowned experts in the field of ultrafast laser spectroscopy, and is still guided by its founder, Prof. George Atkinson (University of Arizona and Science and Technology Advisor to the Secretary of State). In its current format, the conference contributes to traditional areas of time resolved vibrational spectroscopies including infrared, Raman and related laser methods. It combines them with the most recent developments to gain new information for research and novel technical applications. The scientific program addressed basic science, applied research and advancing novel commercial applications. The thirteenth conference on Time Resolved Vibrational Spectroscopy promoted science in the areas of physics, chemistry and biology with a strong focus on biochemistry and material science. Vibrational spectra are molecule- and bond-specific. Thus, time-resolved vibrational studies provide detailed structural and kinetic information about primary dynamical processes on the picometer length scale. From this perspective, the goal of achieving a complete understanding of complex chemical and physical processes on the molecular level is well pursued by the recent progress in experimental and theoretical vibrational studies. These proceedings collect research papers presented at the TRVS XIII in Freising, German

Computational tools for experimental determination and theoretical prediction of protein structure

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. The authors intend to review the state of the art in the experimental determination of protein 3D structure (focus on nuclear magnetic resonance), and in the theoretical prediction of protein function and of protein structure in 1D, 2D and 3D from sequence. All the atomic resolution structures determined so far have been derived from either X-ray crystallography (the majority so far) or Nuclear Magnetic Resonance (NMR) Spectroscopy (becoming increasingly more important). The authors briefly describe the physical methods behind both of these techniques; the major computational methods involved will be covered in some detail. They highlight parallels and differences between the methods, and also the current limitations. Special emphasis will be given to techniques which have application to ab initio structure prediction. Large scale sequencing techniques increase the gap between the number of known proteins sequences and that of known protein structures. They describe the scope and principles of methods that contribute successfully to closing that gap. Emphasis will be given on the specification of adequate testing procedures to validate such methods

Écoulements de solides amorphes : modélisation élastoplastique et théorie de couplage de modes

Contrary to the case of simple fluids, a finite stress is required to initiate the flow of amorphous solids, a broad class of materials ranging from bulk metallic glasses to dense emulsions. The objective of this thesis is to model the flow of these materials in a general framework, with an emphasis on heterogeneities.In a first approach, using the liquid regime as a starting point, I have investigated to what extent inhomogeneities can be accommodated in the framework of the mode-coupling theory of rheology. A generic equation for the evolution of density inhomogeneities has been derived.At low temperatures, the flow is indeed quite heterogeneous: it consists of periods of elastic deformation interspersed with swift localised rearrangements of particles, that induce long-range elastic deformations and can thereby spark off new rearrangements. In a second approach, a model rooted in this scenario has been refined so as to reflect the interplay between the external drive and the localised rearrangements, which is at the origin of the flow curve of athermal solids. The latter has been reproduced satisfactorily.Turning to spatial correlations in the flow, we have shown that there exists no universal scaling for these correlations in elastoplastic models, although a broad class of correlation lengths scale with \dot{\gamma}^{\nicefrac{-1}{d}} in the shear-dominated regime in d dimensions.Besides, shear localisation has been observed in diverse variants of the model, whenever blocks are durably weakened following a plastic event.Finally, we have directly compared model predictions to experimental results on the flow of dense emulsions through microchannels and to athermal molecular dynamics simulations. Spurred on by the observation of some discrepancies, we have developed and implemented a more flexible code, based on a simplified Finite Element routine, which notably provides a better account of structural disorder and inertial effects.À la différence des liquides simples, les solides amorphes, une vaste catégorie de matériaux allant des verres métalliques aux émulsions concentrées, ne se mettent à s'écouler qu'au-delà d'une contrainte finie. Notre thèse a pour objet la modélisation de cet écoulement, dans un cadre général et avec un accent mis sur les hétérogénéités.En premier lieu, notre travail a porté sur l'inclusion d'inhomogénéités dans le cadre de la théorie de couplage de modes appliquée à la rhéologie et nous avons notamment obtenu une équation générale d'évolution des inhomogénéités de densité.À basse température, l'écoulement est en effet fortement hétérogène : des phases de déformation élastique sont entrecoupées de réarrangements de particules, brusques et localisés, qui interagissent par le biais des déformations élastiques qu'ils génèrent. En second lieu, nous avons donc considéré un modèle calqué sur ce scénario et affiné ses éléments constitutifs pour rendre compte de la compétition entre cisaillement appliqué et réarrangements locaux, à l'origine de la courbe d'écoulement des matériaux athermiques. Cette dernière a été reproduite de manière satisfaisante.Pour ce qui est des corrélations spatiales dans l'écoulement, nous avons montré qu'il n'existe pas de loi d'échelle universelle dans les modèles élasto-plastiques, malgré la présence d'une classe de longueurs de corrélation décroissant comme \dot{\gamma}^{\nicefrac{-1}{d}} en d dimensions, dans le régime dominé par le cisaillement.Par ailleurs, dans diverses variantes du modèle, le cisaillement se trouve localisé dans une région du matériau. Ce phénomène apparaît dès lors que les blocs élasto-plastiques sont durablement fragilisés à la suite d'un événement plastique.Enfin, les prédictions du modèle ont été directement mises en regard avec des expériences sur l'écoulement en microcanal d'émulsions concentrées et des simulations de dynamique moléculaire à température nulle. Les écarts observés nous ont poussé à développer et implémenter un code plus flexible, qui s'appuie sur une routine simplifiée d'Éléments Finis et rend mieux compte du désordre structurel et des effets inertiels

Investigation of hidden multipolar spin order in frustrated magnets using interpretable machine learning techniques

Frustration gives rise to a plethora of intricate phenomena, the most salient of which are spin liquids, both classical ones—such as the spin-ice phase which has been realized experimentally in rare-earth oxide pyrochlore materials—and their more elusive quantum counterparts. At low temperatures, classical frustrated spin systems may still order, despite their extensive ground-state degeneracy, due to the order-by-disorder phenomenon. The resulting orders are often of a multipolar type which defies conventional probes. Identifying and characterizing such “hidden” orders is thus a challenging endeavor. This thesis introduces a machine-learning framework for studying the phase diagram of classical frustrated spin models in an unbiased and automated way. The interpretability of the resulting classification was of paramount importance in the design of the method. It allows for the inference of both the order parameter tensors of the phases with broken symmetries as well as the constraints which are characteristic of classical spin liquids and signal their emergent gauge structure. On top of that, it establishes a hierarchical relationship among the various phases according to their degree of disorder. The framework is applied to three different models and spin configurations are harvested from classical Monte Carlo simulations of those. A gauge model is used to mimic the interactions between the mesogens of generalized nematics. These may possess arbitrary point group symmetry, resulting in benchmark models with a low-temperature phase that breaks the O(3) spin symmetry accordingly. In addition, two frustrated spin models are considered. The historically important case of the Heisenberg model on the kagome lattice gives rise to hidden triatic order which requires a description in terms of two tensors of different ranks; the machine is capable of finding both. Meanwhile, for the XXZ model on the pyrochlore lattice, the machine reconstructs the complex phase diagram which was only recently obtained and correctly identifies the spin nematic phase as well as three distinct types of classical spin liquids, including their crossovers. The method has the potential to accelerate the characterization of model Hamiltonians of frustrated magnets. It can scrutinize the whole parameter space at once and may thus help to identify interesting regimes, paving the way for the search of new orders and spin liquids.Frustration führt zu einer Fülle komplexer Phänomene, von denen die herausragendsten Spinflüssigkeiten sind, sowohl klassische – wie beispielsweise die Spin-Eis-Phase, die experimentell in den Oxiden seltener Erden auf dem Pyrochlor-Gitter realisiert wurde – und ihre schwerer fassbaren quantenmechanischen Gegenstücke. Bei niedrigen Temperaturen können klassische frustrierte Spinsysteme obgleich der extensiven Entartung des Grundzustandes aufgrund des Phänomens der „Ordnung durch Unordnung“ dennoch Ordnungen ausbilden. Diese sind oft multipolarer Natur und entziehen sich herkömmlichen Messgrößen. Die Identifikation und Charakterisierung solcher „verborgener“ Ordnungen ist daher eine herausfordernde Aufgabe. In dieser Arbeit wird ein Verfahren für das unvoreingenommene und automatisierte maschinelle Lernen der Phasendiagramme klassischer frustrierter Spinmodelle eingeführt. Die Interpretierbarkeit der resultierenden Klassifikatoren war für das Design der Methode ausschlaggebend. Sie erlaubt den Rückschluss sowohl auf die Ordnungsparametertensoren der symmetriebrechenden Phasen als auch auf die Nebenbedingungen, die für klassische Spinflüssigkeiten charakteristisch sind und auf deren emergente Eichstruktur hindeuten. Darüber hinaus wird eine hierarchische Beziehung zwischen den verschiedenen Phasen gemäß dem Grade ihrer jeweiligen Unordnung hergestellt. Das Verfahren wird auf drei verschiedene Modelle angewendet und Spin-Konfigurationen werden jeweils aus klassischen Monte-Carlo-Simulationen dieser gewonnen. Ein Eichmodell dient dazu, die Wechselwirkungen zwischen den Mesogenen verallgemeinerter nematischer Flüssigkristalle nachzuahmen. Diese können beliebige Punktgruppensymmetrien besitzen, was zu Benchmark-Modellen mit einer Niedertemperaturphase führt, die die O(3)-Spinsymmetrie entsprechend herunterbricht. Darüber hinaus werden zwei frustrierte Spinmodelle betrachtet. Der historisch wichtige Fall des Heisenberg-Modells auf dem Kagome-Gitter führt zu einer verborgenen trigonalen Ordnung, die eine Beschreibung in Form von zwei Tensoren unterschiedlichen Ranges erforderlich macht; die Maschine ist in der Lage, beide zu finden. Währenddessen rekonstruiert die Maschine für das XXZ-Modell auf dem Pyrochlor-Gitter das komplexe Phasendiagramm, das erst vor Kurzem ausgearbeitet wurde, und identifiziert die spin-nematische Phase sowie drei verschiedene Arten klassischer Spinflüssigkeiten, einschließlich ihrer Übergänge, korrekt. Die Methode hat das Potenzial, die Charakterisierung von Spinmodellen frustrierter Magnete zu beschleunigen. Sie kann den gesamten Parameterraum auf einmal untersuchen und somit dazu beitragen, interessante Bereiche zu identifizieren. Dies bereitet den Weg für die Suche nach neuen Ordnungen und Spinflüssigkeiten