Reliability analysis of discrete-state performance functions via adaptive sequential sampling with detection of failure surfaces

The paper presents a new efficient and robust method for rare event probability estimation for computational models of an engineering product or a process returning categorical information only, for example, either success or failure. For such models, most of the methods designed for the estimation of failure probability, which use the numerical value of the outcome to compute gradients or to estimate the proximity to the failure surface, cannot be applied. Even if the performance function provides more than just binary output, the state of the system may be a non-smooth or even a discontinuous function defined in the domain of continuous input variables. In these cases, the classical gradient-based methods usually fail. We propose a simple yet efficient algorithm, which performs a sequential adaptive selection of points from the input domain of random variables to extend and refine a simple distance-based surrogate model. Two different tasks can be accomplished at any stage of sequential sampling: (i) estimation of the failure probability, and (ii) selection of the best possible candidate for the subsequent model evaluation if further improvement is necessary. The proposed criterion for selecting the next point for model evaluation maximizes the expected probability classified by using the candidate. Therefore, the perfect balance between global exploration and local exploitation is maintained automatically. The method can estimate the probabilities of multiple failure types. Moreover, when the numerical value of model evaluation can be used to build a smooth surrogate, the algorithm can accommodate this information to increase the accuracy of the estimated probabilities. Lastly, we define a new simple yet general geometrical measure of the global sensitivity of the rare-event probability to individual variables, which is obtained as a by-product of the proposed algorithm.Comment: Manuscript CMAME-D-22-00532R1 (Computer Methods in Applied Mechanics and Engineering

Advances in Stereo Vision

Stereopsis is a vision process whose geometrical foundation has been known for a long time, ever since the experiments by Wheatstone, in the 19th century. Nevertheless, its inner workings in biological organisms, as well as its emulation by computer systems, have proven elusive, and stereo vision remains a very active and challenging area of research nowadays. In this volume we have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

Industrial Robotics

This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Sensors and Systems for Indoor Positioning

This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications

A hydrodynamical perspective on the turbulent transport of bacteria in rivers

The transport of bacteria in river systems is a phenomenon which occurs on a multitude of length scales ranging from the size of individual microbes up to the size of an entire estuary. At the same time the understanding of the spreading of microbial populations after a localised contamination event such as a combined sewer overflow is crucial for the prediction of the water quality downstream of the source, which is in turn essential to managing public health. It is well-established that microbial populations in fluvial systems may preferably be found on the surface of small particles rather than solely freely suspended in the water body. The attachment to particles provides an environment beneficial to the survival of bacteria due to the improved access to nutrients and the shielding from environmental stressors, but also alters their dispersion characteristics as the transport of bacteria is then coupled to the trajectories of heavy particles. The importance in the distinction between the particle-attached and the freely-suspended mode of transport has been recognised in the mechanistic modelling of bacteria fate and transport. However, due to the multiscale nature of the problem, the mechanisms which govern the transport of particles in river-like flows are never resolved explicitly, and hence, the models profoundly rely upon the availability of accurate descriptions thereof. The associated problem of particles settling in a turbulent carrier flow is an active topic of research by itself, and is rich in emerging phenomena such as the emergence of spatial inhomogeneities or non-trivial modifications of the settling characteristics compared to quiescent environments. In particular, the transient settling of particles in horizontal open channels, which serves as an abstraction of particle-attached bacteria transport in rivers, has hitherto received only little attention in the literature. As a consequence, the knowledge on the impact of its defining features such as boundedness, anisotropy and vertical inhomogeneity on the settling characteristics is limited and needs to be addressed to enable the formulation of reliable models thereof. The aim of this thesis is to fill the knowledge gap on the transport characteristics of heavy particles in turbulent horizontal open channel flows, and to identify phenomena which may be of importance in the context of bacteria transport modelling. For this purpose, the incompressible Navier--Stokes equations and the momentum balance equations for dispersed particles are solved using direct numerical simulations and the immersed boundary method. This approach resolves all relevant scales of turbulence and the microscopic flow around each particle explicitly, and thus, describes the particle-fluid interaction from fundamental principles of physics without the need of additional modelling. Apart from the contaminated particles, which are introduced near the free surface of the flow, the simulation domain includes approximately 100,000 fully resolved particles at the bottom of the domain, which form a realistic sediment bed, and enable the examination of the interaction between contaminated particles and mobile sediments. Concerning the parameter space, the value of the friction Reynolds number is varied within the range $Re_{\tau} \in [241,838]$, while the contaminant parameter space is chosen such that the resulting relative turbulence intensities---defined as the ratio between the friction velocity and the undisturbed terminal velocity---lie within the range $I_{\tau} \in [0.47,2.88]$. Moreover, two types of sediment bedforms are investigated in order to assess their effect on contaminant transport, namely a macroscopically flat bed and a bed featuring ripples. The analysis of the simulation data shows that the settling velocity of the contaminant particles is enhanced in the ensemble-averaged sense, yet, the time from beginning of the settling until the initial deposition is prolonged when compared to the ratio between the channel height and the terminal velocity. The enhancement is demonstrated to be a result of the preferential sampling of turbulent sweep events, which also implies that the streamwise component of the particle velocity is increased compared to the mean fluid velocity at the same position. A closer examination of the spatial organisation of contaminated particles reveals that they tend to accumulate in large-scale high-speed velocity streaks in the outer region of turbulence. Due to this focusing mechanism, the mean-squared lateral displacement of the settling particles stagnates in the lower half of the channel such that contaminants are not further dispersed in cross-stream direction until shortly before deposition. The same behaviour could be reproduced using a time-invariant exact coherent flow state resembling a hairpin vortex as a proxy for turbulence, and an extended parameter sweep in this setup suggests that this transport barrier effect persists even at high relative turbulence intensities. It is speculated that this phenomenon might confine contaminated particles to a region close to the river bank over a considerable downstream distance in the aftermath of a combined sewer overflow event, which might seriously impact decisions regarding public health measures. Near the sediment bed, the barrier effect of the large-scale motions is inactive and contaminants are found to disperse laterally at a rate which presumably depends on the Shields parameter. The interaction between the sediment and the contaminants is distinct for the two bed topologies under investigation. In the case of macroscopically flat beds, the contaminated particles are transported towards sediment ridges which are in turn known to be a result of the action of large-scale fluid motions, and the mixing of contaminants and sediment particles is restricted to the thin layer of sediment near the interface. In contrast, the presence of ripples leads to a capturing effect where contaminated particles are preferentially deposited in the trough of the ripple, and subsequently buried by a thick layer of sediment due to the propagation of the bed feature. This mechanism temporarily immobilises a large share of all contaminated particles until the displacement of the ripple has sufficiently progressed for them to be eroded on the windward side. During the immobilisation, the associated bacteria are shielded from solar radiation to a substantial degree, which likely has a significant impact on their inactivation, especially in shallow waters. Moreover, the cyclic nature of this phenomenon may provide one of many explanations for bacteria storages which are known to exist in river sediments and may cause bursts in fecal bacteria indicator levels even in absence of immediate contamination events. It is concluded that direct numerical simulation can be a valuable tool for the analysis of bacteria transport, and recommendations are made on how the conjectures compiled in this thesis can be targeted in laboratory experiments to examine their relevance

A hydrodynamical perspective on the turbulent transport of bacteria in rivers

The transport of bacteria in turbulent river-like environments is addressed, where bacterial populations are frequently encountered attached to solids. This transport mode is investigated by studying the transient settling of heavy particles in turbulent channel flows featuring sediment beds. A numerical method is used to fully resolve turbulence and finite-size particles, which enables the assessment of the complex interplay between flow structures, suspended solids and river sediment

Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

Coverage Path Planning for Autonomous Robots

Coverage Path Planning (CPP) is a problem of path computation with minimal length that guarantees to scan the entire area of interest. CPP finds its application in diverse fields like cartography, inspection, precision agriculture, milling, and demining. However, this thesis is a prominent step to solve CPP for real-world problems where environment poses multiple challenges. At first, four significant and pressing challenges for CPP in extreme environment are identified. Each challenge is formulated as a problem and its solution has been presented as a dedicated chapter in this thesis. The first problem, Goal-Oriented Sensor based CPP, focuses on cumbersome tasks like Nuclear Decommissioning, where the robot covers an abandoned site in tandem with the goal to reach a static target in minimal time. To meet the grave speeding-up challenge, a novel offline-online strategy is proposed that efficiently models the site using floor plans and grid maps as a priori information. The proposed strategy outperforms the two baseline approaches with reduction in coverage time by 45%- 82%. The second problem explores CPP of distributed regions, applicable in post-disaster scenarios like Fukushima Daiichi. Experiments are conducted at radiation laboratory to identify the constraints robot would be subjected to. The thesis is successfully able to diagnose transient damage in the robot’s sensor after 3 Gy of gamma radiation exposure. Therefore, a region order travel constraint known as Precedence Provision is imposed for successful coverage. The region order constraint allows the coverage length to be minimised by 65% in comparison to state-of-the-art techniques. The third problem identifies the major bottleneck of limited on-board energy that inhibits complete coverage of distributed regions. The existing approaches allow robots to undertake multiple tours for complete coverage which is impractical in many scenarios. To this end, a novel algorithm is proposed that solves a variant of CPP where the robot aims to achieve near-optimal area coverage due to path length limitation caused by the energy constraint. The proposed algorithm covers 23% - 35% more area in comparison to the state-of-the-art approaches. Finally, the last problem, an extension of the second and third problems, deals with the problem of CPP over a set of disjoint regions using a fleet of heterogeneous aerial robots. A heuristic is proposed to deliver solutions within acceptable time limits. The experiments demonstrate that the proposed heuristic solution reduces the energy cost by 15-40% in comparison to the state-of-the art solutions