12 research outputs found

    Centralized Algorithms Based on Clustering with Self-tuning of Parameters for Cooperative Target Observation

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    Clustering on target positions is a class of centralized algorithms used to calculate the surveillance robots' displacements in the Cooperative Target Observation (CTO) problem. This work proposes and evaluates Fuzzy C-means (FCM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) with K-means (DBSk) based self-tuning clustering centralized algorithms for the CTO problem and compares its performances with that of K-means. Two random motion patterns are adopted for the targets: in free space or on a grid. As a contribution, the work allows identifying ranges of problem configuration parameters in which each algorithm shows the highest average performance. As a first conclusion, in the challenging situation in which the relative speed of the targets is high, and the relative sensor range of the surveillance is low, for which the existing algorithms present a substantial drop in performance, the FCM algorithm proposed outperforms the others. Finally, the DBSk algorithm adapts very well in low execution frequency, showing promising results in this challenging situation

    Improving Wildlife Monitoring using a Multi-criteria Cooperative Target Observation Approach

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    Wildlife Monitoring is very important for maintaining sustainability of environment. In this paper we pose Wildlife Monitoring as Cooperative Target Observation (CTO) problem and propose a Multi Criteria Decision Analysis (MCDA) based algorithm named MCDA-CTO, to maximize the observation of different animal species by Unmanned Aerial Vehicles (UAVs) and to effectively handle multiple target types and the multiple criteria that arise due to targets and environmental factors, during decision making. UAVs have uncertainty in observation of targets which makes it challenging to develop a high-quality monitoring strategy. We therefore develop monitoring techniques that explicitly take actions to improve belief about the true type of targets being observed. In wildlife monitoring, it is often reasonable to assume that the observers may themselves be a subject of observation by unknown adversaries (poachers). Randomizing the observer’s actions can therefore help to make the target observation strategy less predictable. We then provide experimental validation that shows that the techniques we develop provide a higher (true positive/true negative) ratio along with better randomization than state of the art approaches

    Cooperative Robots to Observe Moving Targets: Review

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    A Study of the Impact of Interaction Mechanisms and Population Diversity in Evolutionary Multiagent Systems

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    In the Evolutionary Computation (EC) research community, a major concern is maintaining optimal levels of population diversity. In the Multiagent Systems (MAS) research community, a major concern is implementing effective agent coordination through various interaction mechanisms. These two concerns coincide when one is faced with Evolutionary Multiagent Systems (EMAS). This thesis demonstrates a methodology to study the relationship between interaction mechanisms, population diversity, and performance of an evolving multiagent system in a dynamic, real-time, and asynchronous environment. An open sourced extensible experimentation platform is developed that allows plug-ins for evolutionary models, interaction mechanisms, and genotypical encoding schemes beyond the one used to run experiments. Moreover, the platform is designed to scale arbitrarily large number of parallel experiments in multi-core clustered environments. The main contribution of this thesis is better understanding of the role played by population diversity and interaction mechanisms in the evolution of multiagent systems. First, it is shown, through carefully planned experiments in three different evolutionary models, that both interaction mechanisms and population diversity have a statistically significant impact on performance in a system of evolutionary agents coordinating to achieve a shared goal of completing problems in sequential task domains. Second, it is experimentally verified that, in the sequential task domain, a larger heterogeneous population of limited-capability agents will evolve to perform better than a smaller homogeneous population of full-capability agents, and performance is influenced by the ways in which the agents interact. Finally, two novel trait-based population diversity levels are described and are shown to be effective in their applicability

    Using multiple agents in uncertainty minimization of ablating target sources

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    The objective of this research effort is to provide an efficient methodology for a multi-agent robotic system to observe moving targets that are generated from an ablation process. An ablation process is a process where a larger mass is reduced in volume as a result of erosion; this erosion results in smaller, independent masses. An example of such a process is the natural process that gives rise to icebergs, which are generated through an ablation process referred to as ice calving. Ships that operate in polar regions continue to face the threat of floating ice sheets and icebergs generated from the ice ablation process. Although systems have been implemented to track these threats with varying degrees of success, many of these techniques require that the operations are conducted outside of some boundary where the icebergs are known not to drift. Since instances where polar operations must be conducted within such a boundary line do exist (e.g., resource exploration), methods for situational awareness of icebergs for these operations are necessary. In this research, efficacy of these methods is correlated to the initial acquisition time of observing newly ablated targets, as it provides for the ability to enact early countermeasures. To address the research objective, the iceberg tracking problem is defined such that it is re-cast within a class of robotic, multiagent target-observation problems. From this new definition, the primary contributions of this research are obtained: 1) A definition of the iceberg observation problem that extends an existing robotic observation problem to the requirements for the observation of floating ice masses; 2) A method for modeling the activity regions on an ablating source to extract ideal search regions to quickly acquire newly ablated targets; 3) A method for extracting metrics for this model that can be used to assess performance of observation algorithms and perform resource allocation. A robot controller is developed that implements the algorithms that result from these contributions and comparisons are made to existing target acquisition techniques.Ph.D

    Sustainability of systems interoperability in dynamic business networks

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    Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de ComputadoresCollaborative networked environments emerged with the spread of the internet, contributing to overcome past communication barriers, and identifying interoperability as an essential property to support businesses development. When achieved seamlessly, efficiency is increased in the entire product life cycle support. However, due to the different sources of knowledge, models and semantics, enterprise organisations are experiencing difficulties exchanging critical information, even when they operate in the same business environments. To solve this issue, most of them try to attain interoperability by establishing peer-to-peer mappings with different business partners, or use neutral data and product standards as the core for information sharing, in optimized networks. In current industrial practice, the model mappings that regulate enterprise communications are only defined once, and most of them are hardcoded in the information systems. This solution has been effective and sufficient for static environments, where enterprise and product models are valid for decades. However, more and more enterprise systems are becoming dynamic, adapting and looking forward to meet further requirements; a trend that is causing new interoperability disturbances and efficiency reduction on existing partnerships. Enterprise Interoperability (EI) is a well established area of applied research, studying these problems, and proposing novel approaches and solutions. This PhD work contributes to that research considering enterprises as complex and adaptive systems, swayed to factors that are making interoperability difficult to sustain over time. The analysis of complexity as a neighbouring scientific domain, in which features of interoperability can be identified and evaluated as a benchmark for developing a new foundation of EI, is here proposed. This approach envisages at drawing concepts from complexity science to analyse dynamic enterprise networks and proposes a framework for sustaining systems interoperability, enabling different organisations to evolve at their own pace, answering the upcoming requirements but minimizing the negative impact these changes can have on their business environment

    Formation control of nonholonomic mobile robots: the virtual structure approach

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    PhDIn recent years, there has been a considerable growth in applications of multi-robot systems as opposed to single-robot systems. This thesis presents our proposed solutions to a formation control problem in which mobile robots are required to create a desired formation shape and track a desired trajectory as a whole. In the first instance, we study the formation control problem for unicycle mobile robots. We propose two control algorithms based on a cascaded approach: one based on a kinematic model of a robot and the other based on a dynamic model. We also propose a saturated controller in which actuator limitations are explicitly accounted for. To demonstrate how the control algorithms work, we present an extensive simulation and experimental study. Thereafter we move on to formation control algorithms in which the coordination error is explicitly defined. Thus, we are able to give conditions for robots keeping their desired formation shape without necessarily tracking the desired trajectory. We also introduce a controller in which both trajectory tracking and formation shape maintenance are achieved as well as a saturated algorithm. We validate the applicability of the introduced controllers in simulations and experiments. Lastly, we study the formation control problem for car-like robots. In this case we develop a controller using the backstepping technique. We give conditions for robots keeping their desired formation shape while failing to track their desired trajectories and present simulation results to demonstrate the applicability of the proposed controlle

    Design of a protocol for event-based network reconfiguration of active vision systems

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    Projecte final de carrera fet en col.laboració amb Leibniz Universtät HannoverCatalà: Avui en dia la vigilancia de grans àreas, com ara bancs, aeroports o ciutats es basa principalment en sistemas de video. Les Active Cameras (ACs) juguen un paper important per als sistemes de seguretat, ja que combinen video detecció, processament de video i comunicació en un sol dispositiu. Un punt feble és que les ACs son generalment fixes i poden apareixer oclusions que poden crear punts cecs al sistema. Aquests punts cecs poden ser superats mitjançant l?ús de ACs mòbils crean una xarxa mòbil, anomenada Active Camera Network (ACN), presentades en aquesta tesi. No obstant això, la mobilitat de les ACs ve juntament amb desafiaments en termes de coordinació i configuración. A més d?això, el cost de les ACs es més gran en comparació a les xarxes de cameres estatiques, però el nombre de guàrdies necessaris per inspeccionar una gran àrea com una ciutat per exemple o per controlar una gran quantitat de monitors es pot reduir considerablement amb les ACNs. El nostre objectiu és implementar l?arquitectura de un sistema auto-reconfigurable per una xarxa de ACs que poden anar muntades en robots mòbils pel terra o en microvehicles aeris (MAV). Així, les ACs decidirán per si mateixes on actualizar la seva posición per tal d?aconseguir un rendiment òptim del sistema. Per assolir aquest objectiu, les ACs aumentaran o disminuiran les regions espacials redundants amb el seus veïns fent focus en les regions mes sobrecarregades. El protocol presentat en aquesta tesi adapta la posición de les ACs per detectar les diferents trajectories que travessan la zona de vigilancia i que poden evolucionar amb el temps. Les simulacions han demostrat que el protocol presentat augmenta el rendiment general del sistema fins un 190% més gràcies a la reconfiguració i cooperación entre les ACs veïnes.Castellano: Hoy en día la vigilancia de grandes áreas, tales como bancos, aeropuertos o ciudades se basa principalmente en sistemas de video vigilancia. Las Active Cameras (ACs) juegan un papel importante para los sistemas de seguridad, ya que combinan video detección, procesamiento de video y comunicación en un solo dispositivo. Un punto débil es que las ACs son generalmente fijas y pueden aparecer oclusiones que creen puntos ciegos en el sistema. Estos puntos ciegos pueden ser superados mediante el uso de ACs móviles creando una red móvil, llamada Active Camera Network (ACN), presentadas en esta tesis. Sin embargo, la movilidad de las ACs viene junto con desafíos en términos de coordinación y configuración. Además de esto, el coste de las ACs es mayor en comparación a las redes de cámaras estáticas, pero el número de guardias necesarios para inspeccionar una gran área como una ciudad por ejemplo o para controlar una gran cantidad de monitores se puede reducir considerablemente con las ACNs. Nuestro objetivo es implementar la arquitectura de un sistema auto-reconfigurable para una red de ACs que pueden ir montadas en robots móviles por el suelo o en micro vehículos aéreos (MAV). Así, las ACs decidirán por sí mismas donde actualizar sus posiciones con el fin de conseguir un rendimiento óptimo del sistema. Para alcanzar este objetivo, las ACs aumentarán o disminuirán las regiones espaciales redundantes con sus vecinos haciendo foco en las regiones más sobrecargadas. El protocolo presentado en esta tesis adapta la posición de las ACs para detectar las diferentes trayectorias que atraviesan la zona de vigilancia y que pueden evolucionar con el tiempo. Las simulaciones han demostrado que el protocolo presentado aumenta el rendimiento general del sistema hasta un 190% más gracias a la reconfiguración y cooperación entre las ACs vecinas.English: Nowadays surveillance of large areas, such as banks, airports or cities is mostly based on vision systems. Smart Cameras (SCs) play an important role for security systems as they combine video sensing, video processing and communication within a single device. One weak point is that SCs are usually stationary and so occlusions may create blind spots in the system. These blind spots may be overcome by using mobile SCs, so called Active Camera Networks (ACNs), as introduced in this thesis. Nevertheless, mobility of SCs come along with challenges in terms of coordination and configuration. In addition to this, the cost of ACs is higher in comparison to static camera networks but the number of guards needed to survey a large area like a city or to control a lot of monitors can be reduced considerably with AC networks. Our goal is to implement a self-reconfiguration system architecture for networked smart cameras that could be mounted either on mobile robots on the ground or Micro Air Vehicles (MAVs). Thus, the ACs will decide by themselves where to update their position in order to achieve the optimal system's performance. To reach that goal, ACs will increase or decrease spatial redundancy regions with their neighbours to overcome overloaded regions. The protocol presented in this thesis adapts the position of the ACN to the different trajectories that traverse a surveillance area over time. The simulations have shown that the presented protocol increase the overall performance due to the node reconfiguration and cooperation between neighbouring ACs

    A Unified Framework for Solving Multiagent Task Assignment Problems

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    Multiagent task assignment problem descriptors do not fully represent the complex interactions in a multiagent domain, and algorithmic solutions vary widely depending on how the domain is represented. This issue is compounded as related research fields contain descriptors that similarly describe multiagent task assignment problems, including complex domain interactions, but generally do not provide the mechanisms needed to solve the multiagent aspect of task assignment. This research presents a unified approach to representing and solving the multiagent task assignment problem for complex problem domains. Ideas central to multiagent task allocation, project scheduling, constraint satisfaction, and coalition formation are combined to form the basis of the constrained multiagent task scheduling (CMTS) problem. Basic analysis reveals the exponential size of the solution space for a CMTS problem, approximated by O(2n(m+n)) based on the number of agents and tasks involved in a problem. The shape of the solution space is shown to contain numerous discontinuous regions due to the complexities involved in relational constraints defined between agents and tasks. The CMTS descriptor represents a wide range of classical and modern problems, such as job shop scheduling, the traveling salesman problem, vehicle routing, and cooperative multi-object tracking. Problems using the CMTS representation are solvable by a suite of algorithms, with varying degrees of suitability. Solution generating methods range from simple random scheduling to state-of-the-art biologically inspired approaches. Techniques from classical task assignment solvers are extended to handle multiagent task problems where agents can also multitask. Additional ideas are incorporated from constraint satisfaction, project scheduling, evolutionary algorithms, dynamic coalition formation, auctioning, and behavior-based robotics to highlight how different solution generation strategies apply to the complex problem space
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