2,124 research outputs found

    MORPH: A Reference Architecture for Configuration and Behaviour Self-Adaptation

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    An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus, dynamic reconfiguration and discrete event control theory are at the heart of architectural adaptation. Although controlling configuration and behaviour at runtime has been discussed and applied to architectural adaptation, architectures for self-adaptive systems often compound these two aspects reducing the potential for adaptability. In this paper we propose a reference architecture that allows for coordinated yet transparent and independent adaptation of system configuration and behaviour

    Heterogeneous multi-robot system for mapping environmental variables of greenhouses

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    The productivity of greenhouses highly depends on the environmental conditions of crops, such as temperature and humidity. The control and monitoring might need large sensor networks, and as a consequence, mobile sensory systems might be a more suitable solution. This paper describes the application of a heterogeneous robot team to monitor environmental variables of greenhouses. The multi-robot system includes both ground and aerial vehicles, looking to provide flexibility and improve performance. The multi-robot sensory system measures the temperature, humidity, luminosity and carbon dioxide concentration in the ground and at different heights. Nevertheless, these measurements can be complemented with other ones (e.g., the concentration of various gases or images of crops) without a considerable effort. Additionally, this work addresses some relevant challenges of multi-robot sensory systems, such as the mission planning and task allocation, the guidance, navigation and control of robots in greenhouses and the coordination among ground and aerial vehicles. This work has an eminently practical approach, and therefore, the system has been extensively tested both in simulations and field experiments.The research leading to these results has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+ D en la Comunidad de Madrid and co-funded by Structural Funds of the EU, and from the DPI2014-56985-Rproject (Protección robotizada de infraestructuras críticas) funded by the Ministerio de Economía y Competitividad of Gobierno de España. This work is framed on the SAVIER (Situational Awareness Virtual EnviRonment) Project, which is both supported and funded by Airbus Defence & Space. The experiments were performed in an educational greenhouse of the E.T.S.I.Agrónomos of Technical University of Madrid.Peer Reviewe

    Multiple UAV systems: a survey

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    Nowadays, Unmanned Aerial Vehicles (UAVs) are used in many different applications. Using systems of multiple UAVs is the next obvious step in the process of applying this technology for variety of tasks. There are few research works that cover the applications of these systems and they are all highly specialized. The goal of this survey is to fill this gap by providing a generic review on different applications of multiple UAV systems that have been developed in recent years. We also present a nomenclature and architecture taxonomy for these systems. In the end, a discussion on current trends and challenges is provided.This work was funded by the Ministry of Economy, Industryand Competitiveness of Spain under Grant Nos. TRA2016-77012-R and BES-2017-079798Peer ReviewedPostprint (published version

    Formation coordination and network management of UAV networks using particle swarm optimization and software-defined networking

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    In recent years, with the growth in the use of Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. The lack of reliable communication infrastructure in these scenarios has motivated the use of UAVs to establish a network as flying nodes, also known as UAV networks. However, the high mobility degree of flying and terrestrial users may be responsible for constant changes in nodes’ positioning, which makes it more challenging to guarantee their communication during the operational time. In this context, this work presents a framework solution for formation coordination and network management of UAVs, which aims to establish and maintain a set of relays units in order to provide a constant, reliable and efficient communication link among user nodes - which are performing individual or collaborative missions on its turn. Such a framework relies on a set of formation coordination algorithms - including the Particle Swarm Optimization (PSO) evolutionary algorithm -, and also considers the use of Software-defined Networking-based (SDN) communication protocol for network management. For coordination proposes, a novel particle selection criteria is proposed, which aims to guarantee network manageability of UAV formations, therefore being able to guarantee service persistence in case of nodes’ failure occurrence, as well as to provide required network performance, as a consequence. Simulations performed in OMNeT++ show the efficiency of the proposed solution and prove a promising direction of the solution for accomplishing its purposes.Em regiões de confrontos militares, em cenários pós-catástrofes naturais e, inclusive, em grandes áreas de cultivo agrícola, é comum a ausência de uma infra-estrutura préestabelecida de comunicação entre usuários durante a execução de uma ou mais operações eventuais. Nestes casos, Veículos Aéreos Não Tripulados (VANTs) podem ser vistos como uma alternativa para o estabelecimento de uma rede temporária durante essas missões. Para algumas aplicações, a alta mobilidade destes usuários podem trazem grandes desafios para o gerenciamento autônomo de uma estrutura de comunicação aérea, como a organização espacial dos nós roteadores e as políticas de encaminhamento de pacotes adotadas durante a operação. Tendo isso em vista, esse trabalho apresenta o estudo de uma solução que visa o estabelecimento e manutenção das conexões entre os usuários - nos quais executam tarefas individuais ou colaborativas -, através do uso de algoritmos de coordenação de formação - no qual inclui o algoritmo evolucionário Otimização por Enxame de Partículas -, e, também, de conceitos relacionados a Rede Definidas por Software para o gerenciamento da rede. Ainda, é proposto um novo critério de seleção das partículas do algoritmo evolucionário, visando garantir gerenciabilidade das topologias formadas e, consequentemente, a persistência do serviço em caso de falha dos nós roteadores, assim como o cumprimento de especificações desejadas para o desempenho da rede. Simulações em OMNeT++ mostraram a eficácia da proposta e sustentam o modelo proposto a fim de atingir seus objetivos

    Flight coordination solutions for multirotor unmanned aerial vehicles

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    [EN] As the popularity and the number of Unmanned Aerial Vehicles (UAVs) increases, new protocols are needed to coordinate them when flying without direct human control, and to avoid that these UAVs collide with each other. Testing such novel protocols on real UAVs is a complex procedure that requires investing much time, money and research efforts. Hence, it becomes necessary to first test the developed solutions using simulation. Unfortunately, existing tools present significant limitations: some of them only simulate accurately the flight behavior of a single UAV, while some other simulators can manage several UAVs simultaneously, but not in real time, thus losing accuracy regarding the mobility pattern of the UAV. In this work we address such problem by introducing Arducopter Simulator (ArduSim), a novel simulation platform that allows controlling in soft real-time the flight and communications of multiple UAVs, being the developed protocols directly portable to real devices. Moreover, ArduSim includes a realistic model for the WiFi communications link between UAVs, which was proposed based on real experiments. The chances that two UAVs get close to each other during their flights is increasing as more and more of them populate our skies, causing concerns regarding potential collisions. Therefore, this thesis also proposes the Mission Based Collision Avoidance Protocol (MBCAP), a novel UAV collision avoidance protocol applicable to all types of multicopters flying autonomously. It relies on wireless communications in order to detect nearby UAVs, and to negotiate the procedure to avoid any potential collision. Experimental and simulation results demonstrate the validity and effectiveness of the proposed solution, which typically introduces a small overhead in the range of 15 to 42 seconds for each risky situation successfully handled. The previous solution aims at UAVs performing independent flights, but they can also form a swarm, where more constraints have to be met to avoid collisions among them, and to allow them to complete their task efficiently. Deploying an UAV swarm instead of a single UAV can provide additional benefits when, for example, cargo carrying requirements exceed the lifting power of a single UAV, or when the deployment of several UAVs simultaneously can accelerate the accomplishment of the mission, and broaden the covered area. To this aim, in this work we present the Mission-based UAV Swarm Coordination Protocol (MUSCOP), a solution that allows multiple UAVs to perfectly coordinate their flight when performing planned missions. Experimental results show that the proposed protocol is able to achieve a high degree of swarm cohesion independently of the flight formation adopted, and even in the presence of very lossy channels, achieving minimal synchronization delays and very low position offsets with regard to the ideal case. Currently, there are some other scenarios, such as search and rescue operations, where the deployment of manually guided swarms of UAVs can be necessary. In such cases, the pilot's commands are unknown a priori (unpredictable), meaning that the UAVs must respond in near real-time to the movements of the leader UAV in order to maintain swarm consistency. Hence, in this thesis we also propose the FollowMe protocol for the coordination of UAVs in a swarm where the swarm leader is controlled by a real pilot, and the other UAVs must follow it in real-time to maintain swarm cohesion. Simulation results show the validity of the proposed swarm coordination protocol, detailing the responsiveness limits of our solution, and finding the minimum distances between UAVs to avoid collisions.[ES] A medida que la popularidad de los Vehículos Aéreos No Tripulados (VANTs) se incrementa, también se hacen necesarios nuevos protocolos para coordinarlos en vuelos sin control humano directo, y para evitar que colisionen entre sí. Probar estos nuevos protocolos en VANTs reales es un proceso complejo que requiere invertir mucho tiempo, dinero y esfuerzo investigador. Por lo tanto, es necesario probar en simulación las soluciones previamente implementadas. Lamentablemente, las herramientas actuales tienen importantes limitaciones: algunas simulan con precisión el vuelo de un único VANT, mientras que otros simuladores pueden gestionar varios VANTs simultáneamente aunque no en tiempo real, perdiendo por lo tanto precisión en el patrón de movilidad del VANT. En este trabajo abordamos este problema introduciendo Arducopter Simulator (ArduSim), una nueva plataforma de simulación que permite controlar en tiempo real el vuelo y la comunicación entre múltiples VANTs, permitiendo llevar los protocolos desarrollados a dispositivos reales con facilidad. Además, ArduSim incluye un modelo realista de un enlace de comunicaciones WiFi entre VANTs, el cual está basado en el resultado obtenido de experimentos con VANTs reales. La posibilidad de que dos VANTs se aproximen entre sí durante el vuelo se incrementa a medida que hay más aeronaves de este tipo surcando los cielos, introduciendo peligro por posibles colisiones. Por ello, esta tesis propone Mission Based Collision Avoidance Protocol (MBCAP), un nuevo protocolo de evitación de colisiones para VANTs aplicable a todo tipo de multicópteros mientras vuelan autónomamente. MBCAP utiliza comunicaciones inalámbricas para detectar VANTs cercanos y para negociar el proceso de evitación de la colisión. Los resultados de simulaciones y experimentos reales demuestran la validez y efectividad de la solución propuesta, que introduce un pequeño aumento del tiempo de vuelo de entre 15 y 42 segundos por cada situación de riesgo correctamente resuelta. La solución anterior está orientada a VANTs que realizan vuelos independientes, pero también pueden formar un enjambre, donde hay que cumplir más restricciones para evitar que colisionen entre sí, y para que completen la tarea de forma eficiente. Desplegar un enjambre de VANTs en vez de uno solo proporciona beneficios adicionales cuando, por ejemplo, la necesidad de carga excede la capacidad de elevación de un único VANT, o cuando al desplegar varios VANTs simultáneamente se acelera la misión y se cubre un área mayor. Con esta finalidad, en este trabajo presentamos el protocolo Mission-based UAV Swarm Coordination Protocol (MUSCOP), una solución que permite a varios VANTs coordinar perfectamente el vuelo mientras realizan misiones planificadas. Los resultados experimentales muestran que el protocolo propuesto permite al enjambre alcanzar un grado de cohesión elevado independientemente de la formación de vuelo adoptada, e incluso en presencia de un canal de comunicación con muchas pérdidas, consiguiendo retardos en la sincronización insignificantes y desfases mínimos en la posición con respecto al caso ideal. Actualmente hay otros escenarios, como las operaciones de búsqueda y rescate, donde el despliegue de enjambres de VANTs guiados manualmente puede ser necesario. En estos casos, las órdenes del piloto son desconocidas a priori (impredecibles), lo que significa que los VANTs deben responder prácticamente en tiempo real a los movimientos del VANT líder para mantener la consistencia del enjambre. Por ello, en esta tesis proponemos el protocolo FollowMe para la coordinación de VANTs en un enjambre donde el líder es controlado por un piloto, y el resto de VANTs lo siguen en tiempo real para mantener la cohesión del enjambre. Las simulaciones muestran la validez del protocolo de coordinación de enjambres propuesto, detallando los límites de la solución, y definiendo la distancia mínima entre VANTs para evita[CA] A mesura que la popularitat dels Vehicles Aeris No Tripulats (VANTs) s'incrementa, també es fan necessaris nous protocols per a coordinar-los en vols sense control humà directe, i per a evitar que col·lisionen entre si. Provar aquests nous protocols en VANTs reals és un procés complex que requereix invertir molt de temps, diners i esforç investigador. Per tant, és necessari provar en simulació les solucions prèviament implementades. Lamentablement, les eines actuals tenen importants limitacions: algunes simulen amb precisió el vol d'un únic VANT, mentre que altres simuladors poden gestionar diversos VANTs simultàniament encara que no en temps real, perdent per tant precisió en el patró de mobilitat del VANT. En aquest treball abordem aquest problema introduint Arducopter Simulator (ArduSim), una nova plataforma de simulació que permet controlar en temps real el vol i la comunicació entre múltiples VANTs, permetent portar els protocols desenvolupats a dispositius reals amb facilitat. A més, ArduSim inclou un model realista d'un enllaç de comunicacions WiFi entre VANTs, que està basat en el resultat obtingut d'experiments amb VANTs reals. La possibilitat que dues VANTs s'aproximen entre si durant el vol s'incrementa a mesura que hi ha més aeronaus d'aquest tipus solcant els cels, introduint perill per possibles col·lisions. Per això, aquesta tesi proposa Mission Based Collision Avoidance Protocol (MBCAP), un nou protocol d'evitació de col·lisions per a VANTs aplicable a tota mena de multicòpters mentre volen autònomament. MBCAP utilitza comunicacions sense fils per a detectar VANTs pròxims i per a negociar el procés d'evitació de la col·lisió. Els resultats de simulacions i experiments reals demostren la validesa i efectivitat de la solució proposada, que introdueix un xicotet augment del temps de vol de entre 15 i 42 segons per cada situació de risc correctament resolta. La solució anterior està orientada a VANTs que realitzen vols independents, però també poden formar un eixam, on cal complir més restriccions per a evitar que col·lisionen entre si, i perquè completen la tasca de forma eficient. Desplegar un eixam de VANTs en comptes d'un només proporciona beneficis addicionals quan, per exemple, la necessitat de càrrega excedeix la capacitat d'elevació d'un únic VANT, o quan en desplegar diversos VANTs simultàniament s'accelera la missió i es cobreix una àrea major. Amb aquesta finalitat, en aquest treball presentem el protocol Mission-based UAV Swarm Coordination Protocol (MUSCOP), una solució que permet a diversos VANTs coordinar perfectament el vol mentre realitzen missions planificades. Els resultats experimentals mostren que el protocol proposat permet a l'eixam aconseguir un grau de cohesió elevat independentment de la formació de vol adoptada, i fins i tot en presència d'un canal de comunicació amb moltes pèrdues, aconseguint retards en la sincronització insignificants i desfasaments mínims en la posició respecte al cas ideal. Actualment hi ha altres escenaris, com les operacions de cerca i rescat, on el desplegament d'eixams de VANTs guiats manualment pot ser necessari. En aquests casos, les ordres del pilot són desconegudes a priori (impredictibles), el que significa que els VANTs han de respondre pràcticament en temps real als moviments del VANT líder per a mantindre la consistència de l'eixam. Per això, en aquesta tesi proposem el protocol FollowMe per a la coordinació de VANTs en un eixam on el líder és controlat per un pilot, i la resta de VANTs ho segueixen en temps real per a mantindre la cohesió de l'eixam. Les simulacions mostren la validesa del protocol de coordinació d'eixams proposat, detallant els límits de la solució, i definint la distància mínima entre VANTs per a evitar col·lisions.Fabra Collado, FJ. (2020). Flight coordination solutions for multirotor unmanned aerial vehicles [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/147857TESI

    Mission programming for flying ensembles: combining planning with self-organization

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    The application of autonomous mobile robots can improve many situations of our daily lives. Robots can enhance working conditions, provide innovative techniques for different research disciplines, and support rescue forces in an emergency. In particular, flying robots have already shown their potential in many use-cases when cooperating in ensembles. Exploiting this potential requires sophisticated measures for the goal-oriented, application-specific programming of flying ensembles and the coordinated execution of so defined programs. Because different goals require different robots providing different capabilities, several software approaches emerged recently that focus on specifically designed robots. These approaches often incorporate autonomous planning, scheduling, optimization, and reasoning attributable to classic artificial intelligence. This allows for the goal-oriented instruction of ensembles, but also leads to inefficiencies if ensembles grow large or face uncertainty in the environment. By leaving the detailed planning of executions to individuals and foregoing optimality and goal-orientation, the selforganization paradigm can compensate for these drawbacks by scalability and robustness. In this thesis, we combine the advantageous properties of autonomous planning with that of self-organization in an approach to Mission Programming for Flying Ensembles. Furthermore, we overcome the current way of thinking about how mobile robots should be designed. Rather than assuming fixed-design robots, we assume that robots are modifiable in terms of their hardware at run-time. While using such robots enables their application in many different use cases, it also requires new software approaches for dealing with this flexible design. The contributions of this thesis thus are threefold. First, we provide a layered reference architecture for physically reconfigurable robot ensembles. Second, we provide a solution for programming missions for ensembles consisting of such robots in a goal-oriented fashion that provides measures for instructing individual robots or entire ensembles as desired in the specific use case. Third, we provide multiple self-organization mechanisms to deal with the system’s flexible design while executing such missions. Combining different self-organization mechanisms ensures that ensembles satisfy the static requirements of missions. We provide additional self-organization mechanisms for coordinating the execution in ensembles ensuring they meet the dynamic requirements of a mission. Furthermore, we provide a solution for integrating goal-oriented swarm behavior into missions using a general pattern we have identified for trajectory-modification-based swarm behavior. Using that pattern, we can modify, quantify, and further process the emergent effect of varying swarm behavior in a mission by changing only the parameters of its implementation. We evaluate results theoretically and practically in different case studies by deploying our techniques to simulated and real hardware.Der Einsatz von autonomen mobilen Robotern kann viele Abläufe unseres täglichen Lebens erleichtern. Ihr Einsatz kann Arbeitsbedingungen verbessern, als innovative Technik für verschiedene Forschungsdisziplinen dienen oder Rettungskräfte im Einsatz unterstützen. Insbesondere Flugroboter haben ihr Potenzial bereits in vielerlei Anwendungsfällen gezeigt, gerade wenn mehrere in Ensembles eingesetzt werden. Das Potenzial fliegender Ensembles zielgerichtet und anwendungsspezifisch auszuschöpfen erfordert ausgefeilte Programmiermethoden und Koordinierungsverfahren. Zu diesem Zweck sind zuletzt viele unterschiedliche und auf speziell entwickelte Roboter zugeschnittene Softwareansätze entstanden. Diese verwenden oft klassische Planungs-, Scheduling-, Optimierungs- und Reasoningverfahren. Während dies vor allem den zielgerichteten Einsatz von Ensembles ermöglicht, ist es jedoch auch oft ineffizient, wenn die Ensembles größer oder deren Einsatzumgebungen unsicher werden. Die genannten Nachteile können durch das Paradigma der Selbstorganisation kompensiert werden: Falls Anwendungen nicht zwangsläufig auf Optimalität und strikte Zielorientierung ausgelegt sind, kann so Skalierbarkeit und Robustheit im System erreicht werden. In dieser Arbeit werden die vorteilhaften Eigenschaften klassischer Planungstechniken mit denen der Selbstorganisation in einem Ansatz zur Missionsprogrammierung für fliegende Ensembles kombiniert. In der dafür entwickelten Lösung wird von der aktuell etablierten Ansicht einer unveränderlichen Roboterkonstruktion abgewichen. Stattdessen wird die Hardwarezusammenstellung der Roboter als zur Laufzeit modifizierbar angesehen. Der Einsatz solcher Roboter erfordert neue Softwareansätze um mit genannter Flexibilität umgehen zu können. Die hier vorgestellten Beiträge zu diesem Thema lassen sich in drei Punkten zusammenfassen: Erstens wird eine Schichtenarchitektur als Referenz für physikalisch konfigurierbare Roboterensembles vorgestellt. Zweitens wird eine Lösung zur zielorientierten Missions-Programmierung für derartige Ensembles präsentiert, mit der sowohl einzelne Roboter als auch ganze Ensembles instruiert werden können. Drittens werden mehrere Selbstorganisationsmechanismen vorgestellt, die die autonome Ausführung so erstellter Missionen ermöglichen. Durch die Kombination verschiedener Selbstorganisationsmechanismen wird sichergestellt, dass Ensembles die missionsspezifischen Anforderungen erfüllen. Zusätzliche Selbstorganisationsmechanismen ermöglichen die koordinierte Ausführung der Missionen durch die Ensembles. Darüber hinaus bietet diese Lösung die Möglichkeit der Integration zielorientierten Schwarmverhaltens. Durch ein allgemeines algorithmisches Verfahren für auf Trajektorien-Modifikation basierendes Schwarmverhalten können allein durch die Änderung des Parametersatzes unterschiedliche emergente Effekte in einer Mission erzielt, quantifiziert und weiterverarbeitet werden. Zur theoretischen und praktischen Evaluierung der Ergebnisse dieser Arbeit wurden die vorgestellten Techniken in verschiedenen Fallstudien auf simulierter sowie realer Hardware zum Einsatz gebracht
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