POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.

Silicon Photonic Device for Wavelength Sensing and Monitoring

Over the last decade advances and innovations from Silicon Photonics technology were observed in the telecommunications and computing industries. This technology which employs Silicon as an optical medium, relies on current CMOS micro-electronics fabrication processes to enable medium scale integration of many nano-photonic devices to produce photonic integrated circuitry. However, other fields of research such as optical sensor processing can benefit from silicon photonics technology, specially in sensors where the physical measurement is wavelength encoded. In this research work, we present a design and application of a thermally tuned silicon photonic device as an optical sensor interrogator. The main device is a micro-ring resonator filter of 10 $\mu m$ of diameter. A photonic design toolkit was developed based on open source software from the research community. With those tools it was possible to estimate the resonance and spectral characteristics of the filter. From the obtained design parameters, a 7.8 x 3.8 mm optical chip was fabricated using standard micro-photonics techniques. In order to tune a ring resonance, Nichrome micro-heaters were fabricated on top of the device. Some fabricated devices were systematically characterized and their tuning response were determined. From measurements, a ring resonator with a free-spectral-range of 18.4 nm and with a bandwidth of 0.14 nm was obtained. Using just 5 mA it was possible to tune the device resonance up to 3 nm. In order to apply our device as a sensor interrogator in this research, a model of wavelength estimation using time interval between peaks measurement technique was developed and simulations were carried out to assess its performance. To test the technique, an experiment using a Fiber Bragg grating optical sensor was set, and estimations of the wavelength shift of this sensor due to axial strains yield an error within 22 pm compared to measurements from spectrum analyzer. Results from this study implies that signals from FBG sensors can be processed with good accuracy using a micro-ring device with the advantage of ts compact size, scalability and versatility. Additionally, the system also has additional applications such as processing optical wavelength shifts from integrated photonic sensors and to be able to track resonances from laser sources.

Technologies for urban and rural internet of things

Nowadays, application domains such as smart cities, agriculture or intelligent transportation, require communication technologies that combine long transmission ranges and energy efficiency to fulfill a set of capabilities and constraints to rely on. In addition, in recent years, the interest in Unmanned Aerial Vehicles (UAVs) providing wireless connectivity in such scenarios is substantially increased thanks to their flexible deployment. The first chapters of this thesis deal with LoRaWAN and Narrowband-IoT (NB-IoT), which recent trends identify as the most promising Low Power Wide Area Networks technologies. While LoRaWAN is an open protocol that has gained a lot of interest thanks to its simplicity and energy efficiency, NB-IoT has been introduced from 3GPP as a radio access technology for massive machine-type communications inheriting legacy LTE characteristics. This thesis offers an overview of the two, comparing them in terms of selected performance indicators. In particular, LoRaWAN technology is assessed both via simulations and experiments, considering different network architectures and solutions to improve its performance (e.g., a new Adaptive Data Rate algorithm). NB-IoT is then introduced to identify which technology is more suitable depending on the application considered. The second part of the thesis introduces the use of UAVs as flying Base Stations, denoted as Unmanned Aerial Base Stations, (UABSs), which are considered as one of the key pillars of 6G to offer service for a number of applications. To this end, the performance of an NB-IoT network are assessed considering a UABS following predefined trajectories. Then, machine learning algorithms based on reinforcement learning and meta-learning are considered to optimize the trajectory as well as the radio resource management techniques the UABS may rely on in order to provide service considering both static (IoT sensors) and dynamic (vehicles) users. Finally, some experimental projects based on the technologies mentioned so far are presented.

Mechanical design and hybrid control strategies for overconstrained cable-driven parallel robots

Cable-driven parallel robots offer significant advantages in terms of workspace dimensions and payload capability. They are attractive for many industrial tasks to be performed on a large scale, such as handling and manufacturing, without a substantial increase in costs and mechanical complexity with respect to a small-scale application. However, since cables can only sustain tensile stresses, cable tensions must be kept within positive limits during the end-effector motion. This problem can be managed by overconstraining the end-effector and controlling cable tensions. Tension control is typically achieved by mounting a load sensor on all cables, and using specific control algorithms to avoid cable slackness or breakage while the end-effector is controlled in a desired position. These algorithms require multiple cascade control loops and they can be complex and computationally demanding. To simplify the control of overconstrained cable-driven parallel robots, this Thesis proposes suitable mechanical design and hybrid control strategies. It is shown how a convenient design of the cable guidance system allows kinematic modeling to be simplified, without introducing geometric approximations. This guidance system employs swiveling pulleys equipped with position and tension sensors and provides a parallelogram arrangement of cables. Furthermore, a hybrid force/position control in the robot joint space is adopted. According to this strategy, a particular set of cables is chosen to be tension-controlled, whereas the other cables are length-controlled. The force-controlled cables are selected based on the computation of a novel index called force-distribution sensitivity to cable-tension errors. This index aims to evaluate the maximum expected cable-tension error in the length-controlled cables if a unit tension error is committed in the force-controlled cables. In practice, the computation of the force-distribution sensitivity allows determining which cables are best to be force-controlled, to ensure the lowest error in the overall force distribution when a hybrid force/position joint-space strategy is used.

Serverless middlewares to integrate heterogeneous and distributed services in cloud continuum environments

The application of modern ICT technologies is radically changing many fields pushing toward more open and dynamic value chains fostering the cooperation and integration of many connected partners, sensors, and devices. As a valuable example, the emerging Smart Tourism field derived from the application of ICT to Tourism so to create richer and more integrated experiences, making them more accessible and sustainable. From a technological viewpoint, a recurring challenge in these decentralized environments is the integration of heterogeneous services and data spanning multiple administrative domains, each possibly applying different security/privacy policies, device and process control mechanisms, service access, and provisioning schemes, etc. The distribution and heterogeneity of those sources exacerbate the complexity in the development of integrating solutions with consequent high effort and costs for partners seeking them. Taking a step towards addressing these issues, we propose APERTO, a decentralized and distributed architecture that aims at facilitating the blending of data and services. At its core, APERTO relies on APERTO FaaS, a Serverless platform allowing fast prototyping of the business logic, lowering the barrier of entry and development costs to newcomers, (zero) fine-grained scaling of resources servicing end-users, and reduced management overhead. APERTO FaaS infrastructure is based on asynchronous and transparent communications between the components of the architecture, allowing the development of optimized solutions that exploit the peculiarities of distributed and heterogeneous environments. In particular, APERTO addresses the provisioning of scalable and cost-efficient mechanisms targeting: i) function composition allowing the definition of complex workloads from simple, ready-to-use functions, enabling smarter management of complex tasks and improved multiplexing capabilities; ii) the creation of end-to-end differentiated QoS slices minimizing interfaces among application/service running on a shared infrastructure; i) an abstraction providing uniform and optimized access to heterogeneous data sources, iv) a decentralized approach for the verification of access rights to resources.

Cross-sensors analysis of multispectral Earth observation data for environmental monitoring

Time Series Analysis of multispectral satellite data offers an innovative way to extract valuable information of our changing planet. This is now a real option for scientists thanks to data availability as well as innovative cloud-computing platforms, such as Google Earth Engine. The integration of different missions would mitigate known issues in multispectral time series construction, such as gaps due to clouds or other atmospheric effects. With this purpose, harmonization among Landsat-like missions is possible through statistical analysis. This research offers an overview of the different instruments from Landsat and Sentinel missions (TM, ETM, OLI, OLI-2 and MSI sensors) and products levels (Collection-2 Level-1 and Surface Reflectance for Landsat and Level-1C and Level-2A for Sentinel-2). Moreover, a cross-sensors comparison was performed to assess the interoperability of the sensors on-board Landsat and Sentinel-2 constellations, having in mind a possible combined use for time series analysis. Firstly, more than 20,000 pairs of images almost simultaneously acquired all over Europe were selected over a period of several years. The study performed a cross-comparison analysis on these data, and provided an assessment of the calibration coefficients that can be used to minimize differences in the combined use. Four of the most popular vegetation indexes were selected for the study: NDVI, EVI, SAVI and NDMI. As a result, it is possible to reconstruct a longer and denser harmonized time series since 1984, useful for vegetation monitoring purposes. Secondly, the spectral characteristics of the recent Landsat-9 mission were assessed for a combined use with Landsat-8 and Sentinel-2. A cross-sensor analysis of common bands of more than 3,000 almost simultaneous acquisitions verified a high consistency between datasets. The most relevant discrepancy has been observed in the blue and SWIRS bands, often used in vegetation and water related studies. This analysis was supported with spectroradiometer ground measurements.

Enhancing predictive capability of models for solubility and permeability in polymers and composites

The interpretation of phase equilibrium and mass transport phenomena in gas/solvent - polymer system at molten or glassy state is relevant in many industrial applications. Among tools available for the prediction of thermodynamics properties in these systems, at molten/rubbery state, is the group contribution lattice-fluid equation of state (GCLF-EoS), developed by Lee and Danner and ultimately based on Panayiotou and Vera LF theory. On the other side, a thermodynamic approach namely non-equilibrium lattice-fluid (NELF) was proposed by Doghieri and Sarti to consistently extend the description of thermodynamic properties of solute polymer systems obtained through a suitable equilibrium model to the case of non-equilibrium conditions below the glass transition temperature. The first objective of this work is to investigate the phase behaviour in solvent/polymer at glassy state by using NELF model and to develop a predictive tool for gas or vapor solubility that could be applied in several different applications: membrane gas separation, barrier materials for food packaging, polymer-based gas sensors and drug delivery devices. Within the efforts to develop a predictive tool of this kind, a revision of the group contribution method developed by High and Danner for the application of LF model by Panayiotou and Vera is considered, with reference to possible alternatives for the mixing rule for characteristic interaction energy between segments. The work also devotes efforts to the analysis of gas permeability in polymer composite materials as formed by a polymer matrix in which domains are dispersed of a second phase and attention is focused on relation for deviation from Maxwell law as function of arrangement, shape of dispersed domains and loading.

Movement analysis on the field in young football players: biomechanical patterns of performance and injury prevention

The integration of quantitative data from movement analysis technologies is reshaping the analysis of athletes’ performances and injury mitigation, e.g., anterior cruciate ligament (ACL) rupture. Most of the movement assessments are performed in laboratory environments. Recent progress provides the chance to shift the paradigm to a more ecological approach with sport-specific elements and a closer examination of “real” movement patterns associated with performance and (ACL) injury risk. The present PhD thesis aimed at investigating the on-field motion patterns related to performance and injury prevention in young football players. The objectives of the thesis were: (I) in-lab measures of high-dynamics movements were used to validate wearable inertial sensors technology; (II) in-laboratory and on-field agility movement tasks were compared to inspect the effect of football-specific environment; (III) on-field analysis was conducted to challenge wearable sensors technology in the assessment of dangerous movement patterns towards the ACL rupture; (IV) an overview of technologies that could shape present and future assessment of ACL injury risk in daily practice was presented. The validity of wearables in the assessment of high-dynamics movements was confirmed. Relevant differences emerged between the movements performed in a laboratory setting and on the football pitch, supporting the inclusion of an ecological dynamics approach in preventive protocols. The on-field analysis of football-specific movement tasks demonstrated good reliability of wearable sensors and the presence of residual dangerous patterns in the injured players. A tool to inspect at-risk movement patterns on the field through objective measurements was presented. It discussed how potential alternatives to wearable inertial sensors embrace artificial intelligence and closer collaboration between clinical and technical expertise. The present thesis was meant to contribute to setting the basis for data-driven prevention protocols. A deeper comprehension of injury-related principles and counteractions will contribute to preserving athletes’ careers and health over time.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.

Augmented Reality for Airport Control Tower: Analysis and Implementation of Safety Nets

With the development of new technologies, Air Traffic Control, in the nearby of the airport, switched from a purely visual control to the use of radar, sensors and so on. As the industry is switching to the so-called Industry 4.0, also in this frame, it would be possible to implement some of the new tools that can facilitate the work of Air Traffic Controllers. The European Union proposed an innovative project to help the digitalization of the European Sky by means of the Single European Sky ATM Research (SESAR) program, which is the foundation on which the Single European Sky (SES) is based, in order to improve the already existing technologies to transform Air Traffic Management in Europe. Within this frame, the Resilient Synthetic Vision for Advanced Control Tower Air Navigation Service Provision (RETINA) project, which saw the light in 2016, studied the possibility to apply new tools within the conventional control tower to reduce the air traffic controller workload, thanks to the improvements in the augmented reality technologies. After the validation of RETINA, the Digital Technologies for Tower (DTT) project was established and the solution proposed by the University of Bologna aimed, among other things, to introduce Safety Nets in a Head-Up visualization. The aim of this thesis is to analyze the Safety Nets in use within the control tower and, by developing a working concept, implement them in a Head-Up view to be tested by Air Traffic Control Operators (ATCOs). The results, coming from the technical test, show that this concept is working and it could be leading to a future implementation in a real environment, as it improves the air traffic controller working conditions also when low visibility conditions apply.

Construção de um calorímetro isotérmico diferencial de alta sensibilidade e baixo custo

The high cost of sensitivity commercial calorimeters may represent an obstacle for many calorimetric research groups. This work describes the construction and calibration of a batch differential heat conduction calorimeter with sample cells volumes of about 400 μL. The calorimeter was built using two small high sensibility square Peltier thermoelectric sensors and the total cost was estimated to be about US$ 500. The calorimeter was used to study the excess enthalpy of solution of binary mixtures of liquids, as a function of composition, for the following binary systems of solvents: water + 1,4-dioxane or + dimethylsulfoxide at 298,2 ± 0,5 K.

Mensuração da potência mecânica em esforços de alta intensidade na condição laboratorial de corrida atada e na condição de campo em corrida semi-atada e livre

Universidade Estadual de Campinas . Faculdade de Educação Física

Effect of bioglass additions on the sintering of Y-TZP bioceramics

The objective of this work was to evaluate the influence of bioglass additions on the sintering and mechanical properties of yttria-stabilized zirconia ceramics, Y-TZP Samples containing different bioglass additions, varying between 0 and 30 wt.%, were cold uniaxial pressed at 80 MPa and sintered in air at 1200 degrees C or 1300 degrees C for 120 min. Sintered samples were characterized by X-ray Diffractometry and Scanning Electron Microscopy. Hardness and fracture toughness were determined using Vickers indentation method. As a preliminary biological evaluation, in vitro cytotoxicity tests by Neutral Red Uptake method (using mouse connective tissue cells, NCTC clone L929 from ATCC bank) were realized to determine the cytotoxicity level of ZrO(2)-bioglass ceramics. The increasing of bioglass amount leads to the decreasing of relative density due to martensitic (tetragonal-monoclinic) transformation during cooling of the sintered samples. Y-TZP samples sintered at 1300 degrees C containing 5 wt.% of bioglass presented the best results. with high relative density, hardness and fracture toughness of 11.3 GPa and 6.1 MPa m(1/2), respectively. Furthermore, the un-cytotoxic behavior was observed in all sintering conditions and bioglass amounts used in this study. (C) 2009 Elsevier B.V. All rights reserved.

A survey on key management mechanisms for distributed Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have a vast field of applications, including deployment in hostile environments. Thus, the adoption of security mechanisms is fundamental. However, the extremely constrained nature of sensors and the potentially dynamic behavior of WSNs hinder the use of key management mechanisms commonly applied in modern networks. For this reason, many lightweight key management solutions have been proposed to overcome these constraints. In this paper, we review the state of the art of these solutions and evaluate them based on metrics adequate for WSNs. We focus on pre-distribution schemes well-adapted for homogeneous networks (since this is a more general network organization), thus identifying generic features that can improve some of these metrics. We also discuss some challenges in the area and future research directions. (C) 2010 Elsevier B.V. All rights reserved.

Novel blue emitters based on pi-conjugated block copolymers

A series of new phenyl-based conjugated copolymers has been synthesized and investigated by vibrational and photoluminescence spectroscopy (PL). The materials are: poly( 1,4-phenylene-alt-3,6-pyridazine) (COP-PIR), poly(9,9-dioctylfluorene)-co-quaterphenylene (COP-PPP) and poly[(1,4-phenylene-alt-3,6-pyridazine)-co-(1,4-phenylene-alt-9,9-dioctylfluorene)] (COP-PIR-FLUOR), with 3.5% of fluorene. COP-PPP and COP-PIR-FLUOR have high fluorescence quantum yields in solution. Infrared and Raman spectra were used to check the chemical structure of the compounds. The copolymers exhibit blue emission ranging front 2.8 to 3.6 eV when excited at E(exc)=4.13 eV. Stokes-shift Values were estimated on pristine samples in their condensed state from steady-state PL-emission and PL-excitation spectra. They suggest a difference in the torsional angle between the molecular configuration of the polymer blocks at the absorption and PL transitions and also in the photoexcitation diffusion. Additionally, the time-resolved PL of these materials has been investigated by using 100 fs laser pulses at E(exc)=4.64 eV and a streak camera. Results show very fast biexponential kinetics for the two fluorene-based polymers with decay times below 300 ps indicating both intramolecular, fast radiative recombination and migration of photogenerated electron-hole pairs. By contrast, the PL of COP-PIR is less intense and longer lived, indicating that excitons are confined to the chains in this polymer. (C) 2008 Elsevier B.V. All rights reserved.