Defensive swarm: an agent-based modeling analysis

Security at remote military bases is a difficult, yet critical, mission. Remote locations are generally closer to enemy combatants and farther from supporting forces; the individuals charged with defending the bases do so with less equipment. These locations are also usually reliant on air-resupply missions to maintain mission readiness and effectiveness. This thesis analyzes how swarms of small autonomous unmanned aerial vehicles (UAVs) could assist in defensive operations. To accomplish this, I created an agent-based computer simulation model, which creates a tactical problem (enemies attempting to attack or infiltrate a notional base) that a swarm of UAVs attempts to defend against. Results indicate that a swarm can effectively deter 95% of attackers if each UAV is responsible for covering no more than 0.18 square miles and at least 40% of the UAVs are armed. I conclude that UAVs are an excellent addition to base defense and are particularly helpful at remote outposts with less organic capability (limited field of view, defensive assets, etc.). While this research deals specifically with countering a threat to a central base, the algorithms for swarm dynamics could be applied to future problems in mobile convoy or aircraft defense, and even peacetime applications like search and rescue.http://archive.org/details/defensiveswarmng1094556777Major, United States Air ForceApproved for public release; distribution is unlimited

Advances in Supply Chain Management Decision Support Systems: Potential for Improving Decision Support Catalysed by Semantic Interoperability between Systems

Globalization has catapulted ‘cycle time’ as a key indicator of operational efficiency [1] in processes such as supply chain management (SCM). Systems automation holds the promise to augment the ability of supply chain operations or supply networks to rapidly adapt to changes, with minimal human intervention, under ideal conditions. Business communities are emerging as loose federations or organization of networks that may evolve to act as infomediaries in global SCM. These changes, although sluggish, are likely to impact process knowledge and in turn may be stimulated or inhibited by the availability or lack of process interoperability, respectively. The latter will determine operational efficiencies of supply chains. Currently “community of systems” or organization of networks (aligned by industry or business focus) contribute minimally in SCM decisions because true collaboration remains elusive. Convergence and maturity of multiple advances offers the potential for a paradigm shift in interoperability. It may evolve hand-in-hand with [a] the gradual adoption of the semantic web [2] with concomitant development of ontological frameworks, [b] increase in use of multi-agent systems and [c] advent of ubiquitous computing enabling near real-time access to identification of objects and analytics [4]. This paper examines some of these complex trends and related technologies. Irrespective of the characteristics of information systems, the development of various industry-contributed ontologies for knowledge and decision layers, may spur self-organizing networks of business communities and systems to increase their ability to sense and respond, more profitably, through better enterprise and extraprise exchange. In order to transform this vision into reality, systems automation must be weaned from the syntactic web and integrated with the organic growth of the semantic web. Understanding of process semantics and incorporation of intelligent agents with access to ubiquitous near real-time data “bus” are pillars for “intelligent” evolution of decision support systems. Software as infrastructure may integrate plethora of agent colonies through improved architectures (such as, service oriented architecture or SOA) and business communities aligned by industry or service focus may emerge as hubs of such agent empires. However, the feasibility of the path from exciting “pilots” in specific areas toward an informed convergence of systemic real-world implementation remains unclear and fraught with hurdles related to gaps in knowledge transfer from experts in academia to real-world practitioners. The value of interoperability between systems that may catalyse real-time intelligent decision support is further compromised by the lack of clarity of approach and tools. The latter offers significant opportunities for development of tools that may segue to innovative solutions approach. A critical mass of such solutions may spawn the necessary systems architecture for intelligent interoperability, essential for sustainable profitability and productivity in an intensely competitive global economy. This paper addresses some of these issues, tools and solutions that may have broad applicability in several operations including the management of adaptive supply-demand networks [7]

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

Modes of Interaction in Computational Architecture

This thesis is an enquiry into the importance and influence of interaction in architecture, the importance of which is observed through different modes of interaction occurring in various aspects of architectural discourse and practice. Interaction is primarily observed through the different use of software within architectural practice and in the construction of buildings, façades and systems. In turn, the kind of influences software has on architecture is one of the underlying questions of this thesis. Four qualities: Concept, Materiality, Digitization and Interactivity, are proposed as a theoretical base for the analysis and assessment of different aspects of computational architecture. These four qualities permeate and connect the diverse areas of research discussed, including architecture, cybernetics, computer science, interaction design and new media studies, which in combination provide the theoretical background. The modalities of computational architecture analysed here are, digital interior spaces, digitized design processes and communicational exterior environments. The analysis is conducted through case studies: The Fun Palace, Generator Project, Water Pavilion, Tower of Winds, Institute du Monde Arabe, The KPN building, Aegis Hyposurface, BIX Façade, Galleria Department Store, Dexia Tower, and also E:cue, Microstation, Auto-Cad, Rhino, Top Solid and GenerativeComponents software. These are important for discussion because they present different architectural concepts and thoughts about interactivity within architecture. The analytical processes used in the research distinguished and refined, eight modes of interaction: (1) interaction as a participatory process; (2) cybernetic mutualism; (3) thematic interaction; (4) human-computer interaction during architectural design production; (5) interaction during digital fabrication; (6) parametric interaction; (7) kinetic interaction with dynamic architectural forms; and (8) interaction with façades. Out of these, cybernetic mutualism is the mode of interaction proposed by this thesis

Evolutionary Robot Swarms Under Real-World Constraints

Tese de doutoramento em Engenharia Electrotécnica e de Computadores, na especialidade de Automação e Robótica, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Faculdade de Ciências e Tecnologia da Universidade de CoimbraNas últimas décadas, vários cientistas e engenheiros têm vindo a estudar as estratégias provenientes da natureza. Dentro das arquiteturas biológicas, as sociedades que vivem em enxames revelam que agentes simplistas, tais como formigas ou pássaros, são capazes de realizar tarefas complexas usufruindo de mecanismos de cooperação. Estes sistemas abrangem todas as condições necessárias para a sobrevivência, incorporando comportamentos de cooperação, competição e adaptação. Na “batalha” sem fim em prol do progresso dos mecanismos artificiais desenvolvidos pelo homem, a ciência conseguiu simular o primeiro comportamento em enxame no final dos anos oitenta. Desde então, muitas outras áreas, entre as quais a robótica, beneficiaram de mecanismos de tolerância a falhas inerentes da inteligência coletiva de enxames. A área de investigação deste estudo incide na robótica de enxame, consistindo num domínio particular dos sistemas robóticos cooperativos que incorpora os mecanismos de inteligência coletiva de enxames na robótica. Mais especificamente, propõe-se uma solução completa de robótica de enxames a ser aplicada em contexto real. Nesta ótica, as operações de busca e salvamento foram consideradas como o caso de estudo principal devido ao nível de complexidade associado às mesmas. Tais operações ocorrem tipicamente em cenários dinâmicos de elevadas dimensões, com condições adversas que colocam em causa a aplicabilidade dos sistemas robóticos cooperativos. Este estudo centra-se nestes problemas, procurando novos desafios que não podem ser ultrapassados através da simples adaptação da literatura da especialidade em algoritmos de enxame, planeamento, controlo e técnicas de tomada de decisão. As contribuições deste trabalho sustentam-se em torno da extensão do método Particle Swarm Optimization (PSO) aplicado a sistemas robóticos cooperativos, denominado de Robotic Darwinian Particle Swarm Optimization (RDPSO). O RDPSO consiste numa arquitetura robótica de enxame distribuída que beneficia do particionamento dinâmico da população de robôs utilizando mecanismos evolucionários de exclusão social baseados na sobrevivência do mais forte de Darwin. No entanto, apesar de estar assente no caso de estudo do RDPSO, a aplicabilidade dos conceitos aqui propostos não se encontra restrita ao mesmo, visto que todos os algoritmos parametrizáveis de enxame de robôs podem beneficiar de uma abordagem idêntica. Os fundamentos em torno do RDPSO são introduzidos, focando-se na dinâmica dos robôs, nos constrangimentos introduzidos pelos obstáculos e pela comunicação, e nas suas propriedades evolucionárias. Considerando a colocação inicial dos robôs no ambiente como algo fundamental para aplicar sistemas de enxames em aplicações reais, é assim introduzida uma estratégia de colocação de robôs realista. Para tal, a população de robôs é dividida de forma hierárquica, em que são utilizadas plataformas mais robustas para colocar as plataformas de enxame no cenário de forma autónoma. Após a colocação dos robôs no cenário, é apresentada uma estratégia para permitir a criação e manutenção de uma rede de comunicação móvel ad hoc com tolerância a falhas. Esta estratégia não considera somente a distância entre robôs, mas também a qualidade do nível de sinal rádio frequência, redefinindo assim a sua aplicabilidade em cenários reais. Os aspetos anteriormente mencionados estão sujeitos a uma análise detalhada do sistema de comunicação inerente ao algoritmo, para atingir uma implementação mais escalável do RDPSO a cenários de elevada complexidade. Esta elevada complexidade inerente à dinâmica dos cenários motivaram a ultimar o desenvolvimento do RDPSO, integrando para o efeito um mecanismo adaptativo baseado em informação contextual (e.g., nível de atividade do grupo). Face a estas considerações, o presente estudo pode contribuir para expandir o estado-da-arte em robótica de enxame com algoritmos inovadores aplicados em contexto real. Neste sentido, todos os métodos propostos foram extensivamente validados e comparados com alternativas, tanto em simulação como com robôs reais. Para além disso, e dadas as limitações destes (e.g., número limitado de robôs, cenários de dimensões limitadas, constrangimentos reais limitados), este trabalho contribui ainda para um maior aprofundamento do estado-da-arte, onde se propõe um modelo macroscópico capaz de capturar a dinâmica inerente ao RDPSO e, até certo ponto, estimar analiticamente o desempenho coletivo dos robôs perante determinada tarefa. Em suma, esta investigação pode ter aplicabilidade prática ao colmatar a lacuna que se faz sentir no âmbito das estratégias de enxames de robôs em contexto real e, em particular, em cenários de busca e salvamento.Over the past decades, many scientists and engineers have been studying nature’s best and time-tested patterns and strategies. Within the existing biological architectures, swarm societies revealed that relatively unsophisticated agents with limited capabilities, such as ants or birds, were able to cooperatively accomplish complex tasks necessary for their survival. Those simplistic systems embrace all the conditions necessary to survive, thus embodying cooperative, competitive and adaptive behaviours. In the never-ending battle to advance artificial manmade mechanisms, computer scientists simulated the first swarm behaviour designed to mimic the flocking behaviour of birds in the late eighties. Ever since, many other fields, such as robotics, have benefited from the fault-tolerant mechanism inherent to swarm intelligence. The area of research presented in this Ph.D. Thesis focuses on swarm robotics, which is a particular domain of multi-robot systems (MRS) that embodies the mechanisms of swarm intelligence into robotics. More specifically, this Thesis proposes a complete swarm robotic solution that can be applied to real-world missions. Although the proposed methods do not depend on any particular application, search and rescue (SaR) operations were considered as the main case study due to their inherent level of complexity. Such operations often occur in highly dynamic and large scenarios, with harsh and faulty conditions, that pose several problems to MRS applicability. This Thesis focuses on these problems raising new challenges that cannot be handled appropriately by simple adaptation of state-of-the-art swarm algorithms, planning, control and decision-making techniques. The contributions of this Thesis revolve around an extension of the Particle Swarm Optimization (PSO) to MRS, denoted as Robotic Darwinian Particle Swarm Optimization (RDPSO). The RDPSO is a distributed swarm robotic architecture that benefits from the dynamical partitioning of the whole swarm of robots by means of an evolutionary social exclusion mechanism based on Darwin’s survival-of-the-fittest. Nevertheless, although currently applied solely to the RDPSO case study, the applicability of all concepts herein proposed is not restricted to it, since all parameterized swarm robotic algorithms may benefit from a similar approach The RDPSO is then proposed and used to devise the applicability of novel approaches. The fundamentals around the RDPSO are introduced by focusing on robots’ dynamics, obstacle avoidance, communication constraints and its evolutionary properties. Afterwards, taking the initial deployment of robots within the environment as a basis for applying swarm robotics systems into real-world applications, the development of a realistic deployment strategy is proposed. For that end, the population of robots is hierarchically divided, wherein larger support platforms autonomously deploy smaller exploring platforms in the scenario, while considering communication constraints and obstacles. After the deployment, a way of ensuring a fault-tolerant multi-hop mobile ad hoc communication network (MANET) is introduced to explicitly exchange information needed in a collaborative realworld task execution. Such strategy not only considers the maximum communication range between robots, but also the minimum signal quality, thus refining the applicability to real-world context. This is naturally followed by a deep analysis of the RDPSO communication system, describing the dynamics of the communication data packet structure shared between teammates. Such procedure is a first step to achieving a more scalable implementation by optimizing the communication procedure between robots. The highly dynamic characteristics of real-world applications motivated us to ultimate the RDPSO development with an adaptive strategy based on a set of context-based evaluation metrics. This thesis contributes to the state-of-the-art in swarm robotics with novel algorithms for realworld applications. All of the proposed approaches have been extensively validated in benchmarking tasks, in simulation, and with real robots. On top of that, and due to the limitations inherent to those (e.g., number of robots, scenario dimensions, real-world constraints), this Thesis further contributes to the state-of-the-art by proposing a macroscopic model able to capture the RDPSO dynamics and, to some extent, analytically estimate the collective performance of robots under a certain task. It is the author’s expectation that this Ph.D. Thesis may shed some light into bridging the reality gap inherent to the applicability of swarm strategies to real-world scenarios, and in particular to SaR operations.FCT - SFRH/BD /73382/201

A review of UAV autonomous navigation in GPS-denied environments

Unmanned aerial vehicles (UAVs) have drawn increased research interest in recent years, leading to a vast number of applications, such as, terrain exploration, disaster assistance and industrial inspection. Unlike UAV navigation in outdoor environments that rely on GPS (Global Positioning System) for localization, indoor navigation cannot rely on GPS due to the poor quality or lack of signal. Although some reviewing papers particularly summarized indoor navigation strategies (e.g., Visual-based Navigation) or their specific sub-components (e.g., localization and path planning) in detail, there still lacks a comprehensive survey for the complete navigation strategies that cover different technologies. This paper proposes a taxonomy which firstly classifies the navigation strategies into Mapless and Map-based ones based on map usage and then, respectively categorizes the Mapless navigation into Integrated, Direct and Indirect approaches via common characteristics. The Map-based navigation is then split into Known Map/Spaces and Map-building via prior knowledge. In order to analyze these navigation strategies, this paper uses three evaluation metrics (Path Length, Deviation Rate and Exploration Efficiency) according to the common purposes of navigation to show how well they can perform. Furthermore, three representative strategies were selected and 120 flying experiments conducted in two reality-like simulated indoor environments to show their performances against the evaluation metrics proposed in this paper, i.e., the ratio of Successful Flight, the Mean time of Successful Flight, the Mean Length of Successful Flight, the Mean time of Flight, and the Mean Length of Flight. In comparison to the CNN-based Supervised Learning (directly maps visual observations to UAV controls) and the Frontier-based navigation (necessitates continuous global map generation), the experiments show that the CNN-based Distance Estimation for navigation trades off the ratio of Successful Flight and the required time and path length. Moreover, this paper identifies the current challenges and opportunities which will drive UAV navigation research in GPS-denied environments

Cellulo: Tangible Haptic Swarm Robots for Learning

Robots are steadily becoming one of the significant 21st century learning technologies that aim to improve education within both formal and informal environments. Such robots, called Robots for Learning, have so far been utilized as constructionist tools or social agents that aided learning from distinct perspectives. This thesis presents a novel approach to Robots for Learning that aims to explore new added values by means of investigating uses for robots in educational scenarios beyond those that are commonly tackled: We develop a platform from scratch to be "as versatile as pen and paper", namely as composed of easy to use objects that feel like they belong in the learning ecosystem while being seamlessly usable across many activities that help teach a variety of subjects. Following this analogy, we design our platform as many low-cost, palm-sized tangible robots that operate on printed paper sheets, controlled by readily available mobile computers such as smartphones or tablets. From the learners' perspective, our robots are thus physical and manipulable points of hands-on interaction with learning activities where they play the role of both abstract and concrete objects that are otherwise not easily represented. We realize our novel platform in four incremental phases, each of which consists of a development stage and multiple subsequent validation stages. First, we develop accurately positioned tangibles, characterize their localization performance and test the learners' interaction with our tangibles in a playful activity. Second, we integrate mobility into our tangibles and make them full-blown robots, characterize their locomotion performance and test the emerging notion of moving vs. being moved in a learning activity. Third, we enable haptic feedback capability on our robots, measure their range of usability and test them within a complete lesson that highlights this newly developed affordance. Fourth, we develop the means of building swarms with our haptic-enabled tangible robots and test the final form of our platform in a lesson co-designed with a teacher. Our effort thus contains the participation of more than 370 child learners over the span of these phases, which leads to the initial insights into this novel Robots for Learning avenue. Besides its main contributions to education, this thesis further contributes to a range of research fields related to our technological developments, such as positioning systems, robotic mechanism design, haptic interfaces and swarm robotics

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Cyber Law and Espionage Law as Communicating Vessels

Professor Lubin\u27s contribution is Cyber Law and Espionage Law as Communicating Vessels, pp. 203-225. Existing legal literature would have us assume that espionage operations and “below-the-threshold” cyber operations are doctrinally distinct. Whereas one is subject to the scant, amorphous, and under-developed legal framework of espionage law, the other is subject to an emerging, ever-evolving body of legal rules, known cumulatively as cyber law. This dichotomy, however, is erroneous and misleading. In practice, espionage and cyber law function as communicating vessels, and so are better conceived as two elements of a complex system, Information Warfare (IW). This paper therefore first draws attention to the similarities between the practices – the fact that the actors, technologies, and targets are interchangeable, as are the knee-jerk legal reactions of the international community. In light of the convergence between peacetime Low-Intensity Cyber Operations (LICOs) and peacetime Espionage Operations (EOs) the two should be subjected to a single regulatory framework, one which recognizes the role intelligence plays in our public world order and which adopts a contextual and consequential method of inquiry. The paper proceeds in the following order: Part 2 provides a descriptive account of the unique symbiotic relationship between espionage and cyber law, and further explains the reasons for this dynamic. Part 3 places the discussion surrounding this relationship within the broader discourse on IW, making the claim that the convergence between EOs and LICOs, as described in Part 2, could further be explained by an even larger convergence across all the various elements of the informational environment. Parts 2 and 3 then serve as the backdrop for Part 4, which details the attempt of the drafters of the Tallinn Manual 2.0 to compartmentalize espionage law and cyber law, and the deficits of their approach. The paper concludes by proposing an alternative holistic understanding of espionage law, grounded in general principles of law, which is more practically transferable to the cyber realmhttps://www.repository.law.indiana.edu/facbooks/1220/thumbnail.jp