889 resultados para Robotics design framework
Resumo:
In this thesis, we deal with the design of experiments in the drug development process, focusing on the design of clinical trials for treatment comparisons (Part I) and the design of preclinical laboratory experiments for proteins development and manufacturing (Part II). In Part I we propose a multi-purpose design methodology for sequential clinical trials. We derived optimal allocations of patients to treatments for testing the efficacy of several experimental groups by also taking into account ethical considerations. We first consider exponential responses for survival trials and we then present a unified framework for heteroscedastic experimental groups that encompasses the general ANOVA set-up. The very good performance of the suggested optimal allocations, in terms of both inferential and ethical characteristics, are illustrated analytically and through several numerical examples, also performing comparisons with other designs proposed in the literature. Part II concerns the planning of experiments for processes composed of multiple steps in the context of preclinical drug development and manufacturing. Following the Quality by Design paradigm, the objective of the multi-step design strategy is the definition of the manufacturing design space of the whole process and, as we consider the interactions among the subsequent steps, our proposal ensures the quality and the safety of the final product, by enabling more flexibility and process robustness in the manufacturing.
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Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.
Resumo:
The dissertation starts by providing a description of the phenomena related to the increasing importance recently acquired by satellite applications. The spread of such technology comes with implications, such as an increase in maintenance cost, from which derives the interest in developing advanced techniques that favor an augmented autonomy of spacecrafts in health monitoring. Machine learning techniques are widely employed to lay a foundation for effective systems specialized in fault detection by examining telemetry data. Telemetry consists of a considerable amount of information; therefore, the adopted algorithms must be able to handle multivariate data while facing the limitations imposed by on-board hardware features. In the framework of outlier detection, the dissertation addresses the topic of unsupervised machine learning methods. In the unsupervised scenario, lack of prior knowledge of the data behavior is assumed. In the specific, two models are brought to attention, namely Local Outlier Factor and One-Class Support Vector Machines. Their performances are compared in terms of both the achieved prediction accuracy and the equivalent computational cost. Both models are trained and tested upon the same sets of time series data in a variety of settings, finalized at gaining insights on the effect of the increase in dimensionality. The obtained results allow to claim that both models, combined with a proper tuning of their characteristic parameters, successfully comply with the role of outlier detectors in multivariate time series data. Nevertheless, under this specific context, Local Outlier Factor results to be outperforming One-Class SVM, in that it proves to be more stable over a wider range of input parameter values. This property is especially valuable in unsupervised learning since it suggests that the model is keen to adapting to unforeseen patterns.
Resumo:
This thesis deals with robust adaptive control and its applications, and it is divided into three main parts. The first part is about the design of robust estimation algorithms based on recursive least squares. First, we present an estimator for the frequencies of biased multi-harmonic signals, and then an algorithm for distributed estimation of an unknown parameter over a network of adaptive agents. In the second part of this thesis, we consider a cooperative control problem over uncertain networks of linear systems and Kuramoto systems, in which the agents have to track the reference generated by a leader exosystem. Since the reference signal is not available to each network node, novel distributed observers are designed so as to reconstruct the reference signal locally for each agent, and therefore decentralizing the problem. In the third and final part of this thesis, we consider robust estimation tasks for mobile robotics applications. In particular, we first consider the problem of slip estimation for agricultural tracked vehicles. Then, we consider a search and rescue application in which we need to drive an unmanned aerial vehicle as close as possible to the unknown (and to be estimated) position of a victim, who is buried under the snow after an avalanche event. In this thesis, robustness is intended as an input-to-state stability property of the proposed identifiers (sometimes referred to as adaptive laws), with respect to additive disturbances, and relative to a steady-state trajectory that is associated with a correct estimation of the unknown parameter to be found.
Resumo:
Nowadays, one of the most ambitious challenges in soft robotics is the development of actuators capable to achieve performance comparable to skeletal muscles. Scientists have been working for decades, inspired by Nature, to mimic both their complex structure and their perfectly balanced features in terms of linear contraction, force-to-weight ratio, scalability and flexibility. The present Thesis, contextualized within the FET open Horizon 2020 project MAGNIFY, aims to develop a new family of innovative flexible actuators in the field of soft-robotics. For the realization of this actuator, a biomimetic approach has been chosen, drawing inspiration from skeletal muscle. Their hierarchical fibrous structure was mimicked employing the electrospinning technique, while the contraction of sarcomeres was designed employing chains of molecular machines, supramolecular systems capable of performing movements useful to execute specific tasks. The first part deals with the design and production of the basic unit of the artificial muscle, the artificial myofibril, consisting in a novel electrospun core-shell nanofiber, with elastomeric shell and electrically conductive core, coupled with a conductive coating, for the realization of which numerous strategies have been investigated. The second part deals instead with the integration of molecular machines (provided by the project partners) inside these artificial myofibrils, preceded by the study of several model molecules, aimed at simulating the presence of these molecular machines during the initial phases of the project. The last part concerns the realization of an electrospun multiscale hierarchical structure, aimed at reproducing the entire muscle morphology and fibrous organization. These research will be joined together in the near future like the pieces of a puzzle, recreating the artificial actuator most similar to biological muscle ever made, composed of millions of artificial myofibrils, electrically activated in which the nano-scale movement of molecular machines will be incrementally amplified to the macro-scale contraction of the artificial muscle.
Resumo:
Existing bridges built in the last 50 years face challenges due to states far different than those envisaged when they were designed, due to increased loads, ageing of materials, and poor maintenance. For post-tensioned bridges, the need emerged for reliable engineering tools for the evaluation of their capacity in case of steel corrosion due to lack of mortar injection. This can lead to sudden brittle collapses, highlighting the need for proper maintenance and monitoring. This thesis proposes a peak strength model for corroded strands, introducing a “group coefficient” that aims at considering corrosion variability in the wires constituting the strands. The application of the introduced model in a deterministic approach leads to the proposal of strength curves for corroded strands, which represent useful engineering tools for estimating their maximum strength considering both geometry of the corrosion and steel material parameters. Together with the proposed ultimate displacement curves, constitutive laws of the steel material reduced by the effects of corrosion can be obtained. The effects of corroded strands on post-tensioned beams can be evaluated through the reduced bending moment-curvature diagram accounting for these reduced stress-strain relationships. The application of the introduced model in a probabilistic approach allows to estimate peak strength probability functions and consecutive design-oriented safety factors to consider corrosion effects in safety assessment verifications. Both approaches consider two procedures that are based on the knowledge level of the corrosion in the strands. On the sidelines of this main research line, this thesis also presents a study of a seismic upgrading intervention of a case-study bridge through HDRB isolators providing a simplified procedure for the identification of the correct device. The study also investigates the effects due to the variability of the shear modulus of the rubber material of the HDRB isolators on the structural response of the isolated bridge.
Resumo:
This doctoral dissertation represents a cluster of research activities carried out at the DICAM Department of the University of Bologna during a three-year Ph.D. course. The goal of this research is to show how the development of an interconnected infrastructure network, aimed at promoting accessibility and sustainability of places, is fundamental in a framework of deep urban regeneration. Sustainable urban mobility plays an important role in improving the quality of life of citizens. From an environmental point of view, a sustainable mobility system means reducing fuel discharges and energy waste and, in general, aims to promote low carbon emissions. At the same time, a socially and economically sustainable mobility system should be accessible to everybody and create more job opportunities through better connectivity and mobility. Environmentally friendly means of transport such as non-motorized transport, electric vehicles, and hybrid vehicles play an important role in achieving sustainability but require a planned approach at the local policy level. The aim of this study is to demonstrate that, through a targeted reconnection of road and cycle-pedestrian routes, the quality of life of an urban area subject to degradation can be significantly improved just by increasing its accessibility and sustainability. Starting from a detailed study of the European policies and from the comparison with real similar cases, the case study of the Canal Port of Rimini (Italy) has been analysed within the European project FRAMESPORT. The analysis allowed the elaboration of a multicriterial methodology to get to the definition of a project proposal and of a priority scale of interventions. The applied methodology is a valuable tool that may be used in the future in similar urban contexts. Finally, the whole project was represented by using virtual reality to visually show the difference between the before and after the regeneration intervention.
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Nowadays, the chemical industry has reached significant goals to produce essential components for human being. The growing competitiveness of the market caused an important acceleration in R&D activities, introducing new opportunities and procedures for the definition of process improvement and optimization. In this dynamicity, sustainability is becoming one of the key aspects for the technological progress encompassing economic, environmental protection and safety aspects. With respect to the conceptual definition of sustainability, literature reports an extensive discussion of the strategies, as well as sets of specific principles and guidelines. However, literature procedures are not completely suitable and applicable to process design activities. Therefore, the development and introduction of sustainability-oriented methodologies is a necessary step to enhance process and plant design. The definition of key drivers as support system is a focal point for early process design decisions or implementation of process modifications. In this context, three different methodologies are developed to support design activities providing criteria and guidelines in a sustainable perspective. In this framework, a set of key Performance Indicators is selected and adopted to characterize the environmental, safety, economic and energetic aspects of a reference process. The methodologies are based on heat and material balances and the level of detailed for input data are compatible with available information of the specific application. Multiple case-studies are defined to prove the effectiveness of the methodologies. The principal application is the polyolefin productive lifecycle chain with particular focus on polymerization technologies. In this context, different design phases are investigated spanning from early process feasibility study to operative and improvements assessment. This flexibility allows to apply the methodologies at any level of design, providing supporting guidelines for design activities, compare alternative solutions, monitor operating process and identify potential for improvements.
Resumo:
The Internet of Things (IoT) has grown rapidly in recent years, leading to an increased need for efficient and secure communication between connected devices. Wireless Sensor Networks (WSNs) are composed of small, low-power devices that are capable of sensing and exchanging data, and are often used in IoT applications. In addition, Mesh WSNs involve intermediate nodes forwarding data to ensure more robust communication. The integration of Unmanned Aerial Vehicles (UAVs) in Mesh WSNs has emerged as a promising solution for increasing the effectiveness of data collection, as UAVs can act as mobile relays, providing extended communication range and reducing energy consumption. However, the integration of UAVs and Mesh WSNs still poses new challenges, such as the design of efficient control and communication strategies. This thesis explores the networking capabilities of WSNs and investigates how the integration of UAVs can enhance their performance. The research focuses on three main objectives: (1) Ground Wireless Mesh Sensor Networks, (2) Aerial Wireless Mesh Sensor Networks, and (3) Ground/Aerial WMSN integration. For the first objective, we investigate the use of the Bluetooth Mesh standard for IoT monitoring in different environments. The second objective focuses on deploying aerial nodes to maximize data collection effectiveness and QoS of UAV-to-UAV links while maintaining the aerial mesh connectivity. The third objective investigates hybrid WMSN scenarios with air-to-ground communication links. One of the main contribution of the thesis consists in the design and implementation of a software framework called "Uhura", which enables the creation of Hybrid Wireless Mesh Sensor Networks and abstracts and handles multiple M2M communication stacks on both ground and aerial links. The operations of Uhura have been validated through simulations and small-scale testbeds involving ground and aerial devices.
Resumo:
This Thesis wants to highlight the importance of ad-hoc designed and developed embedded systems in the implementation of intelligent sensor networks. As evidence four areas of application are presented: Precision Agriculture, Bioengineering, Automotive and Structural Health Monitoring. For each field is reported one, or more, smart device design and developing, in addition to on-board elaborations, experimental validation and in field tests. In particular, it is presented the design and development of a fruit meter. In the bioengineering field, three different projects are reported, detailing the architectures implemented and the validation tests conducted. Two prototype realizations of an inner temperature measurement system in electric motors for an automotive application are then discussed. Lastly, the HW/SW design of a Smart Sensor Network is analyzed: the network features on-board data management and processing, integration in an IoT toolchain, Wireless Sensor Network developments and an AI framework for vibration-based structural assessment.
Resumo:
Da anni ormai siamo inconsapevolmente "in guerra" con la natura. Sfruttiamo e sprechiamo risorse naturali senza alcuna considerazione per le conseguenze. Le città sono considerate le principali fonti dei problemi ambientali e la regolamentazione del consumo energetico urbano è fondamentale per affrontare il cambiamento climatico globale. DERNetSoft Inc, start-up californiana, ha intravisto il problema come un’opportunità per creare un proprio business il cui scopo è quello di contribuire a costruire un futuro a basse emissioni di carbonio, fornendo un servizio tecnologico scalabile e conveniente per consentire la riduzione delle emissioni di gas a effetto serra a livello mondiale. Per farlo vengono utilizzati i concetti di DER Energy e Aggregation Energy. Nel volume di tesi si affrontano e descrivono la progettazione di un’applicazione mobile, multipiattaforma, sviluppata con il framework React Native. L’app sviluppata è supportata da un’architettura basata su dei micro servizi implementati tramite il cloud di Google. La principale funzionalità dell’applicazione sviluppata è quella di notificare gli utenti di un evento ELRP che, attraverso incentivi economici, promuove la riduzione del consumo energetico durante i periodi di forte stress o emergenza della rete elettrica.
Resumo:
Many sonification systems face a number of common design challenges. These are addressed in every project with different, specific-purpose solutions. We present Panson – an interactive sonification framework implemented in Python that can ease the development of sonification systems. Panson allows the user to implement sonifications using the sc3nb library as interface to the SuperCollider sound synthesis engine. The framework provides support for both offline and online (real-time) sonification through a set of composable classes; these classes are designed to natively support interaction in Jupyter Notebooks. Using Panson, we will show an example of its application by implementing a facial expression sonification Jupyter Notebook based on OpenFace 2.0.
Resumo:
Child marriage is still a great issue in developing countries and even if the interventions to prevent it are having results, they are not enough to eliminate the problem. Among the strategies that seem to work most to fight child marriage, there is the empowerment of girls with information combined with education of parents and community. As smartphones are more accessible year after year in developing countries, this thesis wants to investigate if a mobile app could be effective in fighting child marriage and which characteristics such an app should have. The research was organized in four phases and used design and creation and case study methodologies. Firstly, the literature was analyzed and an initial design was proposed. Secondly, expert interviews were performed to gain feedback on the proposed design, and afterwards prototype was built. Thirdly, a case study in the Democratic Republic of Congo (DRC) was performed to test the prototype, gaining insights and improvements through group interviews with 26 girls aged 15-19. Finally, a first version of the app was developed and a second phase of the case study was run in the DRC to understand if the girls were able to use the app. This phase included 14 girls of which 6 had participated in the prototype testing and used questionnaires as a data generation method. The app was built following the Principles for Digital Development. Even if this app is built based on the case study in DRC is modular and easily adaptable to other contexts as it is not content-specific. It was shown that is worth continuing to study this topic and it was defined a conceptual framework for designing learning apps for developing countries, in particular, to fight child, early, and forced marriage.
Resumo:
Questo volume di tesi ha l'obiettivo di descrivere l'intero processo di progettazione, sviluppo e rilascio di un'applicazione mobile, coinvolgendo anche gli end-user nella fase finale di valutazione. In particolare, il volume di tesi si sviluppa su quattro capitoli che descrivono 1) l'analisi dei requisiti, seguendo un approccio AGILE, 2) l'analisi del ciclo di vita del prodotto (inclusi business model e business plan), 3) l'architettura del sistema, e, infine, 4) la valutazione dell’usabilità e della UX. L'applicazione usata come caso di studio è "LetsBox!", un'applicazione mobile della categoria puzzle game, sviluppata sfruttando il framework di sviluppo di app ibride IONIC 5, con l’obiettivo di creare un gioco che coinvolgesse il giocatore tanto da farlo giocare nei suoi momenti di svago e indurlo a sfidare i record esistenti ma, nello stesso tempo creare un gioco originale e non esistente sul mercato.
Resumo:
La tesi si incentra nello studio e utilizzo del linguaggio Scala per aspetti di ingestion, processing e plotting di dati, prestando enfasi su time series. Questa è costituita da una prima parte introduttiva sui principali argomenti, per poi concentrarsi sull’analisi dei requisiti, il modello del dominio, il design architetturale e la sua implementazione. Termina infine con qualche nota conclusiva riguardante possibili sviluppi futuri. La parte progettuale consiste nello sviluppo di un’applicazione che supporti le librerie scelte e che favorisca il processo in modo agevole. La validazione del progetto software realizzato viene fatta tramite una sequenza di varie configurazioni a dimostrarne la differenza tra la scelta di determinate opzioni: ciascuna viene accompagnata da una o pi`u immagini che ne dimostrano i risultati ottenuti a seguito dell’uso del programma.