Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.

Extracting Urban Food Potential: design-based methods for digital and bodily cartography

Sweden’s recent report on Urban Sustainable Development calls out a missing link between the urban design process and citizens. This paper investigates if engaging citizens as design agents by providing a platform for alternate participation can bridge this gap, through the transfer of spatial agency and new modes of critical cartography. To assess whether this is the case, the approaches are applied to Stockholm’s urban agriculture movement in a staged intervention. The aim of the intervention was to engage citizens in locating existing and potential places for growing food and in gathering information from these sites to inform design in urban agriculture. The design-based methodologies incorporated digital and bodily interfaces for this cartography to take place. The Urban CoMapper, a smartphone digital app, captured real-time perspectives through crowd-sourced mapping. In the bodily cartography, participant’s used their bodies to trace the site and reveal their sensorial perceptions. The data gathered from these approaches gave way to a mode of artistic research for exploring urban agriculture, along with inviting artists to be engaged in the dialogues. In sum, results showed that a combination of digital and bodily approaches was necessary for a critical cartography if we want to engage citizens holistically into the urban design process as spatial agents informing urban policy. Such methodologies formed a reflective interrogation and encouraged a new intimacy with nature, in this instance, one that can transform our urban conduct by questioning our eating habits: where we get our food from and how we eat it seasonally.

Transport magnetischer Partikel durch maßgeschneiderte magnetische Feldlandschaften zur Anwendung in mikrofluidischen Mischprozessen

Die Miniaturisierung von konventioneller Labor- und Analysetechnik nimmt eine zentrale Rolle im Bereich der allgemeinen Lebenswissenschaften und medizinischen Diagnostik ein. Neuartige und preiswerte Technologieplattformen wie Lab-on-a-Chip (LOC) oder Mikrototalanalysesysteme (µTAS) versprechen insbesondere im Bereich der Individualmedizin einen hohen gesellschaftlichen Nutzen zur frühzeitigen und nichtinvasiven Diagnose krankheitsspezifischer Indikatoren. Durch den patientennahen Einsatz preiswerter und verlässlicher Mikrochips auf Basis hoher Qualitätsstandards entfallen kostspielige und zeitintensive Zentrallaboranalysen, was gleichzeitig Chancen für den globalen Einsatz - speziell in Schwellen- und Entwicklungsländern - bietet. Die technischen Herausforderungen bei der Realisierung moderner LOC-Systeme sind in der kontrollierten und verlässlichen Handhabung kleinster Flüssigkeitsmengen sowie deren diagnostischem Nachweis begründet. In diesem Kontext wird der erfolgreichen Integration eines fernsteuerbaren Transports von biokompatiblen, magnetischen Mikro- und Nanopartikeln eine Schlüsselrolle zugesprochen. Die Ursache hierfür liegt in der vielfältigen Einsetzbarkeit, die durch die einzigartigen Materialeigenschaften begründet sind. Diese reichen von der beschleunigten, aktiven Durchmischung mikrofluidischer Substanzvolumina über die Steigerung der molekularen Interaktionsrate in Biosensoren bis hin zur Isolation und Aufreinigung von krankheitsspezifischen Indikatoren. In der Literatur beschriebene Ansätze basieren auf der dynamischen Transformation eines makroskopischen, zeitabhängigen externen Magnetfelds in eine mikroskopisch veränderliche potentielle Energielandschaft oberhalb magnetisch strukturierter Substrate, woraus eine gerichtete und fernsteuerbare Partikelbewegung resultiert. Zentrale Kriterien, wie die theoretische Modellierung und experimentelle Charakterisierung der magnetischen Feldlandschaft in räumlicher Nähe zur Oberfläche der strukturierten Substrate sowie die theoretische Beschreibung der Durchmischungseffekte, wurden jedoch bislang nicht näher beleuchtet, obwohl diese essentiell für ein detailliertes Verständnis der zu Grunde liegenden Mechanismen und folglich für einen Markteintritt zukünftiger Geräte sind. Im Rahmen der vorgestellten Arbeit wurde daher ein neuartiger Ansatz zur erfolgreichen Integration eines Konzepts zum fernsteuerbaren Transport magnetischer Partikel zur Anwendung in modernen LOC-Systemen unter Verwendung von magnetisch strukturierten Exchange-Bias (EB) Dünnschichtsystemen verfolgt. Die Ergebnisse zeigen, dass sich das Verfahren der ionenbe-schussinduzierten magnetischen Strukturierung (IBMP) von EB-Systemen zur Herstellung von maßgeschneiderten magnetischen Feldlandschaften (MFL) oberhalb der Substratoberfläche, deren Stärke und räumlicher Verlauf auf Nano- und Mikrometerlängenskalen gezielt über die Veränderung der Materialparameter des EB-Systems via IBMP eingestellt werden kann, eignet. Im Zuge dessen wurden erstmals moderne, experimentelle Verfahrenstechniken (Raster-Hall-Sonden-Mikroskopie und rastermagnetoresistive Mikroskopie) in Kombination mit einem eigens entwickelten theoretischen Modell eingesetzt, um eine Abbildung der MFL in unterschiedlichen Abstandsbereichen zur Substratoberfläche zu realisieren. Basierend auf der quantitativen Kenntnis der MFL wurde ein neuartiges Konzept zum fernsteuerbaren Transport magnetischer Partikel entwickelt, bei dem Partikelgeschwindigkeiten im Bereich von 100 µm/s unter Verwendung von externen Magnetfeldstärken im Bereich weniger Millitesla erzielt werden können, ohne den magnetischen Zustand des Substrats zu modifizieren. Wie aus den Untersuchungen hervorgeht, können zudem die Stärke des externen Magnetfelds, die Stärke und der Gradient der MFL, das magnetfeldinduzierte magnetische Moment der Partikel sowie die Größe und der künstlich veränderliche Abstand der Partikel zur Substratoberfläche als zentrale Einflussgrößen zur quantitativen Modifikation der Partikelgeschwindigkeit genutzt werden. Abschließend wurde erfolgreich ein numerisches Simulationsmodell entwickelt, das die quantitative Studie der aktiven Durchmischung auf Basis des vorgestellten Partikeltransportkonzepts von theoretischer Seite ermöglicht, um so gezielt die geometrischen Gegebenheiten der mikrofluidischen Kanalstrukturen auf einem LOC-System für spezifische Anwendungen anzupassen.

UNITRAN: A Principle-Based Approach to Machine Translation

Machine translation has been a particularly difficult problem in the area of Natural Language Processing for over two decades. Early approaches to translation failed since interaction effects of complex phenomena in part made translation appear to be unmanageable. Later approaches to the problem have succeeded (although only bilingually), but are based on many language-specific rules of a context-free nature. This report presents an alternative approach to natural language translation that relies on principle-based descriptions of grammar rather than rule-oriented descriptions. The model that has been constructed is based on abstract principles as developed by Chomsky (1981) and several other researchers working within the "Government and Binding" (GB) framework. Thus, the grammar is viewed as a modular system of principles rather than a large set of ad hoc language-specific rules.

Learning-Based Approach to Real Time Tracking and Analysis of Faces

This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.

Model-Based Matching by Linear Combinations of Prototypes

We describe a method for modeling object classes (such as faces) using 2D example images and an algorithm for matching a model to a novel image. The object class models are "learned'' from example images that we call prototypes. In addition to the images, the pixelwise correspondences between a reference prototype and each of the other prototypes must also be provided. Thus a model consists of a linear combination of prototypical shapes and textures. A stochastic gradient descent algorithm is used to match a model to a novel image by minimizing the error between the model and the novel image. Example models are shown as well as example matches to novel images. The robustness of the matching algorithm is also evaluated. The technique can be used for a number of applications including the computation of correspondence between novel images of a certain known class, object recognition, image synthesis and image compression.

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data. It contains four classes corresponding to the four different types of compositional and positive geometry (including the Aitchison geometry). It provides means for computation, plotting and high-level multivariate statistical analysis in all four geometries. These geometries are treated in an fully analogous way, based on the principle of working in coordinates, and the object-oriented programming paradigm of R. In this way, called functions automatically select the most appropriate type of analysis as a function of the geometry. The graphical capabilities include ternary diagrams and tetrahedrons, various compositional plots (boxplots, barplots, piecharts) and extensive graphical tools for principal components. Afterwards, ortion and proportion lines, straight lines and ellipses in all geometries can be added to plots. The package is accompanied by a hands-on-introduction, documentation for every function, demos of the graphical capabilities and plenty of usage examples. It allows direct and parallel computation in all four vector spaces and provides the beginner with a copy-and-paste style of data analysis, while letting advanced users keep the functionality and customizability they demand of R, as well as all necessary tools to add own analysis routines. A complete example is included in the appendix

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

A new all-round density functional based on spin states and SN2 barriers

We report here a new empirical density functional that is constructed based on the performance of OPBE and PBE for spin states and SN 2 reaction barriers and how these are affected by different regions of the reduced gradient expansion. In a previous study [Swart, Sol̀, and Bickelhaupt, J. Comput. Methods Sci. Eng. 9, 69 (2009)] we already reported how, by switching between OPBE and PBE, one could obtain both the good performance of OPBE for spin states and reaction barriers and that of PBE for weak interactions within one and the same (SSB-sw) functional. Here we fine tuned this functional and include a portion of the KT functional and Grimme's dispersion correction to account for π- π stacking. Our new SSB-D functional is found to be a clear improvement and functions very well for biological applications (hydrogen bonding, π -π stacking, spin-state splittings, accuracy of geometries, reaction barriers)

A hybrid approach of knowledge-based reasoning for structural assessment

La idea básica de detección de defectos basada en vibraciones en Monitorización de la Salud Estructural (SHM), es que el defecto altera las propiedades de rigidez, masa o disipación de energía de un sistema, el cual, altera la respuesta dinámica del mismo. Dentro del contexto de reconocimiento de patrones, esta tesis presenta una metodología híbrida de razonamiento para evaluar los defectos en las estructuras, combinando el uso de un modelo de la estructura y/o experimentos previos con el esquema de razonamiento basado en el conocimiento para evaluar si el defecto está presente, su gravedad y su localización. La metodología involucra algunos elementos relacionados con análisis de vibraciones, matemáticas (wavelets, control de procesos estadístico), análisis y procesamiento de señales y/o patrones (razonamiento basado en casos, redes auto-organizativas), estructuras inteligentes y detección de defectos. Las técnicas son validadas numérica y experimentalmente considerando corrosión, pérdida de masa, acumulación de masa e impactos. Las estructuras usadas durante este trabajo son: una estructura tipo cercha voladiza, una viga de aluminio, dos secciones de tubería y una parte del ala de un avión comercial.

Computationally reliable approaches of contractive MPC for discrete-time systems

La tesis pretende explorar acercamientos computacionalmente confiables y eficientes de contractivo MPC para sistemas de tiempo discreto. Dos tipos de contractivo MPC han sido estudiados: MPC con coacción contractiva obligatoria y MPC con una secuencia contractiva de conjuntos controlables. Las técnicas basadas en optimización convexa y análisis de intervalos son aplicadas para tratar MPC contractivo lineal y no lineal, respectivamente. El análisis de intervalos clásicos es ampliado a zonotopes en la geometría para diseñar un conjunto invariante de control terminal para el modo dual de MPC. También es ampliado a intervalos modales para tener en cuenta la modalidad al calcula de conjuntos controlables robustos con una interpretación semántica clara. Los instrumentos de optimización convexa y análisis de intervalos han sido combinados para mejorar la eficacia de contractive MPC para varias clases de sistemas de tiempo discreto inciertos no lineales limitados. Finalmente, los dos tipos dirigidos de contractivo MPC han sido aplicados para controlar un Torneo de Fútbol de Copa Mundial de Micro Robot (MiroSot) y un Tanque-Reactor de Mezcla Continua (CSTR), respectivamente.

Research based design: competition proposal for the Cyprus news agency

The paper attempts to explore the interrelation between a) the architects’ individualism and “pre-structures” b) research- based findings during the design process through experimentation and c)an integrated design approach, where morphology, construction and bioclimatic design are integrated from an early design stage. Through a thorough presentation and analysis of a competition proposal for the Cyprus News Agency, we discuss a number of important findings in relation to the present and possibly future form of the design studio. We suggest that the designer’s “prestructures” may not only be the basis for creative action, but also the basis for understanding and interpretation. Design informed and enriched at every stage by a research-based process, might well be the transmission and transformation of “prestructures”, a process of elaboration and discovery which facilitates and enhances design creativity and possibly allows for a multiplicity of approaches through a range of possibilities. Furthermore, an integrated approach from the early stages of the design process facilitates innovation in materials and systems.

A geomatics-based approach for the derivation of the spatial distribution of sediment transport processes in periglacial mountain environments

Within this paper modern techniques such as satellite image analysis and tools provided by geographic information systems (GIS.) are exploited in order to extend and improve existing techniques for mapping the spatial distribution of sediment transport processes. The processes of interest comprise mass movements such as solifluction, slope wash, dirty avalanches and rock- and boulder falls. They differ considerably in nature and therefore different approaches for the derivation of their spatial extent are required. A major challenge is addressing the differences between the comparably coarse resolution of the available satellite data (Landsat TM/ETM+, 30 in x 30 m) and the actual scale of sediment transport in this environment. A three-stepped approach has been developed which is based on the concept of Geomorphic Process Units (GPUs): parameterization, process area delineation and combination. Parameters include land cover from satellite data and digital elevation model derivatives. Process areas are identified using a hierarchical classification scheme utilizing thresholds and definition of topology. The approach has been developed for the Karkevagge in Sweden and could be successfully transferred to the Rabotsbekken catchment at Okstindan, Norway using similar input data. Copyright (C) 2008 John Wiley & Sons, Ltd.

Projected gradient approach to the numerical solution of the SCoTLASS

The SCoTLASS problem-principal component analysis modified so that the components satisfy the Least Absolute Shrinkage and Selection Operator (LASSO) constraint-is reformulated as a dynamical system on the unit sphere. The LASSO inequality constraint is tackled by exterior penalty function. A globally convergent algorithm is developed based on the projected gradient approach. The algorithm is illustrated numerically and discussed on a well-known data set. (c) 2004 Elsevier B.V. All rights reserved.