A geometrical sink-based cooperative coverage hole recovery strategy for WSNs

© 2015 IEEE. Unlike sporadic node failures, coverage holes emerging from multiple temporally-correlated node failures can severely affect quality of service in a network and put the integrity of entire wireless sensor networks at risk. Conventional topology control schemes addressing such undesirable topological changes have usually overlooked the status of participating nodes in the recovery process with respect to the deployed sink node(s) in the network. In this paper, a cooperative coverage hole recovery model is proposed which utilises the simple geometrical procedure of circle inversion. In this model, autonomous nodes consider their distances to the deployed sink node(s) in addition to their local status, while relocating towards the coverage holes. By defining suitable metrics, the performance of our proposed model performance is compared with a force-based approach

Neuro-Dominating Set Scheme for a Fast and Efficient Robot Deployment in Internet of Robotic Things

International audienceInternet of Robotic Things (IoRT) is a new concept introduced for the first time by ABI Research. Unlike the Internet of Things (IoT), IoRT provides an active sensorization and is considered as the new evolution of IoT. In this context, we propose a Neuro-Dominating Set algorithm (NDS) to efficiently deploy a team of mobile wireless robots in an IoRT scenario, in order to reach a desired inter-robot distance, while maintaining global connectivity in the whole network. We use the term Neuro-Dominating Set to describe our approach, since it is inspired by both neural network and dominating set principles. With NDS algorithm, a robot adopts different behaviors according whether it is a dominating or a dominated robot. Our main goal is to show and demonstrate the beneficial effect of using different behaviors in the IoRT concept. The obtained results show that the proposed method outperforms an existing related technique (i.e., the Virtual Angular Force approach) and the neural network based approach presented in our previous work. As an objective, we aim to decrease the overall traveled distance and keep a low energy consumption level, while maintaining network connectivity and an acceptable convergence time

Biconnecting a network of mobile robots using virtual angular forces

Abstract—This paper proposes a new solution to the problem of self-deploying a network of wireless mobile robots with simultaneous consideration to several criteria, that are, the fault-tolerance (biconnectivity) of the resulting network, its coverage, its diameter, and the quantity of movement required to complete the deployment. These criteria have already been addressed individually in previous works, but we propose here an elegant solution to address all of them at once. Our approach is based on combining two complementary sets of virtual forces: spring forces, whose properties are well known to provide optimal coverage at reasonable movement cost, and angular forces, a new type of force proposed here whose effect is to rotate two angularly consecutive neighbors toward one another when the corresponding angle is larger than 60 ◦ (even if these nodes are not direct neighbors). Angular forces have the global effect of biconnecting the network and reducin

Biconnecting a network of mobile robots using virtual angular forces

International audienceThis paper proposes a new solution to the problem of self-deploying a network of wireless mobile robots with simultaneous consideration to several criteria, that are, the fault-tolerance (\emph{biconnectivity}) of the resulting network, its \emph{coverage}, its \emph{diameter}, and the {\em quantity of movement} required to complete the deployment. These criteria have already been addressed individually in previous works, but we propose here an elegant solution to address all of them at once. Our approach is based on combining two complementary sets of virtual forces: \emph{spring} forces, whose properties are well known to provide optimal coverage at reasonable movement cost, and \emph{angular} forces, a new type of force proposed here whose effect is to rotate two {\em angularly consecutive} neighbors of a node toward one another when the corresponding angle is larger than $60^\circ$ (even if these two nodes are not themselves neighbors). Angular forces have the global effect of biconnecting the network and reducing its diameter, while not affecting the benefits obtained by spring forces on coverage. In this paper we give a detailed description of both types of forces, whose combination poses a number of technical challenges. We also provide an implementation that relies only on position exchanges within two hops. Extensive simulations are finally presented to evaluate the solution against all criteria (coverage, biconnectivity, quantity of movements, and diameter), and show its advantages over prior solutions

Controle de topologia em redes de robôs móveis cooperativos utilizando consenso

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2015.Em grupos de robôs móveis cooperativos, os chamados sistemas multi-robôs, a comunicação é um fator de extrema importância para a correta alocação e realização das tarefas. Essa comunicação é determinada diretamente pela disposição geográfica dos robôs uns em relação aos outros, a chamada topologia de comunicação. O controle da topologia de comunicação em um grupo de robôs permite que certas características da rede de comunicação sejam enfatizadas ou anuladas de acordo com a movimentação dos robôs que a compõem. Neste trabalho são apresentadas duas abordagens para controle de topologia em redes de robôs móveis, em função de quais propriedades dessas redes se deseja exaltar: o controle de topologia para a minimização da comunicação, que possibilita a redução do consumo de energia e da interferência causada pelos processos de comunicação; e o controle de topologia para a manutenção da conectividade, que garante condições para a não desconexão da rede, mesmo que esta esteja sob a influência de instabilidades. Através de um controle de conectividade baseado em consenso, a ação dos algoritmos de controle da topologia é aplicada aos robôs de maneira descentralizada, garantindo que as propriedades desejadas ocorram. São realizados simulações e testes com robôs reais, comprovando a eficiência dos algoritmos propostos em garantir as propriedades topológicas a eles associadas.Abstract : In cooperative robot systems, also known as multi-robot systems, the communication is an extremely important factor for the correct allocation and execution of the robot tasks. This communication is directly determined by the geographic position of the robots in relation each other, which is called communication topology. The topology control can be used to change aspects of the communication topology, allowing that some network characteristics are canceled or exalted, according with the robot's movement in the network. This work presents two approaches for topology control in mobile robot networks that ensure certain properties: the topology control for minimization of the communication, reducing the consumption of energy and the interference caused by radio communication; and the topology control for the connectivity maintenance, ensuring conditions for do not disconnection, even under unstable environments. Through of a connectivity control based on consensus, the action of topology control algorithms is applied to the robots in a decentralized way, ensuring the existence of the desired properties. Finally, are made simulations and tests with real robots, proving the efficiency of the proposed algorithms to ensure the functions assigned to them

Applications et services DTN pour flotte collaborative de drones

Les travaux présentés dans cette thèse effectuée au LaBRI portent sur la mise en place d une flotte de drones et le portage sur celle-ci d applications collaboratives distribuées utilisant des communications asynchrones non sûres. Ces applications sont formalisées grâce au modèle de réétiquetage de graphes Asynchronous Dynamicity Aware Graph Relabeling System (ADAGRS) que nous proposons. Au delà des contributions théoriques, ces travaux ont débouché sur la mise en place du démonstrateur CARUS dans lequel cinq drones se partagent la surveillance d'une grille de 15 points d incidents potentiels (au sol).Lorsqu un drone détecte un incident, il s'en rapproche pour le traiter. Le reste de la flotte doit alors prendre en charge les points que ce drone ne traite plus.Les réorganisations nécessaires de la flotte se font en totale autonomie vis-à-vis du sol et sous hypothèse de perte éventuelle de drones et de messages.The work presented in this thesis, carried out at LaBRI, deals with the set up of a fleet of UAVs and the porting on it of distributed collaborative applications that use unsafe asynchronous communications. These applications are modeled with Asynchronous Dynamicity Aware Graph Relabeling System (ADAGRS), the formal model based on graph relabellings that we propose.Beyond the theoretical contributions, this work led to the development of the CARUS demonstrator in which five UAVs share the supervision of a grid of 15 points of potential ground incidents.When a UAV detects an incident, it comes close to it in order to deal with it. The rest of the fleet must then take care of the points that this UAV no longer visits.The necessary reorganizations of the fleet are done in total autonomy with respect to the ground and under the hypothesis of possible loss of UAVs and messages.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

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