A swarm solution for a cooperative and self-organized team of UAVs to search targets

Paula, Patrícia de; Castro, Miguel; Paillard, Gabriel; Sarmento, Wellington W. F.

doi:10.1109/eatis.2016.7520118

Cited by 13 publications

(3 citation statements)

References 18 publications

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“…Maintaining the connectivity and controlling the distance between multiple UAVs is one of the main challenges in employing cooperative UAVs [89]. Maximizing the coverage area [90], cooperative carrying task [91], [92], searching and localizing a target [93] are among the tasks that can be done by multiple UAVs.…”

Section: B Mobility Optimization For Aerial Bssmentioning

confidence: 99%

Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

Fotouhi

Qiang

Ding

et al. 2019

IEEE Commun. Surv. Tutorials

822

485

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The rapid growth of consumer Unmanned Aerial Vehicles (UAVs) is creating promising new business opportunities for cellular operators. On the one hand, UAVs can be connected to cellular networks as new types of user equipment, therefore generating significant revenues for the operators that can guarantee their stringent service requirements. On the other hand, UAVs offer the unprecedented opportunity to realize UAVmounted flying base stations that can dynamically reposition themselves to boost coverage, spectral efficiency, and user quality of experience. Indeed, the standardization bodies are currently exploring possibilities for serving commercial UAVs with cellular networks. Industries are beginning to trial early prototypes of flying base stations or user equipments, while academia is in full swing researching mathematical and algorithmic solutions to address interesting new problems arising from flying nodes in cellular networks. In this article, we provide a comprehensive survey of all of these developments promoting smooth integration of UAVs into cellular networks. Specifically, we survey (i) the types of consumer UAVs currently available off-the-shelf, (ii) the interference issues and potential solutions addressed by standardization bodies for serving aerial users with the existing terrestrial base stations, (iii) the challenges and opportunities for assisting cellular communications with UAV-based flying relays and base stations, (iv) the ongoing prototyping and test bed activities, (v) the new regulations being developed to manage the commercial use of UAVs, and (vi) the cyber-physical security of UAV-assisted cellular communications.

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Section: B Mobility Optimization For Aerial Bssmentioning

confidence: 99%

Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

Fotouhi

Qiang

Ding

et al. 2019

IEEE Commun. Surv. Tutorials

822

485

View full text Add to dashboard Cite

show abstract

“…These challenges generate in the swarm characteristics robustness and reliability to the system allowing to perform tasks such as exploration and location of targets. In navigation task, there is a great variety of algorithms such as presented in [17] which addresses the characteristics of different algorithms based on swarm intelligence found in nature, such as ant colony, swarm of bees, and wolf pack, among others. The characteristics of the different algorithms generate a great variety of possibilities to choose according to the needs of the challenge.…”

Section: Related Workmentioning

confidence: 99%

Robot Swarm Navigation and Victim Detection Using Rendezvous Consensus in Search and Rescue Operations

Cardona

Calderón

2019

Applied Sciences

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Cooperative behaviors in multi-robot systems emerge as an excellent alternative for collaboration in search and rescue tasks to accelerate the finding survivors process and avoid risking additional lives. Although there are still several challenges to be solved, such as communication between agents, power autonomy, navigation strategies, and detection and classification of survivors, among others. The research work presented by this paper focuses on the navigation of the robot swarm and the consensus of the agents applied to the victims detection. The navigation strategy is based on the application of particle swarm theory, where the robots are the agents of the swarm. The attraction and repulsion forces that are typical in swarm particle systems are used by the multi-robot system to avoid obstacles, keep group compact and navigate to a target location. The victims are detected by each agent separately, however, once the agents agree on the existence of a possible victim, these agents separate from the general swarm by creating a sub-swarm. The sub-swarm agents use a modified rendezvous consensus algorithm to perform a formation control around the possible victims and then carry out a consensus of the information acquired by the sensors with the aim to determine the victim existence. Several experiments were conducted to test navigation, obstacle avoidance, and search for victims. Additionally, different situations were simulated with the consensus algorithm. The results show how swarm theory allows the multi-robot system navigates avoiding obstacles, finding possible victims, and settling down their possible use in search and rescue operations.

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“…In this way, the evolution of CA was confirmed by the increasing number of publications from 2002 onwards with the publication of 5 articles, which is the smallest number of publications per year and in 2017 with 29 articles, the largest number of publications. KEYWORDS: Autonomic Computing, MAPE-K Model, Self-Management.1 | INTRODUÇÃOCom o aumento da complexidade dos sistemas computacionais com arquiteturas orientadas a serviços e compostas por elementos de software e hardware, busca-se transferir responsabilidades de gerenciamento para o próprio sistema.Nesse cenário, novas características foram se tornando cada vez mais importantes, como o dinamismo para que as aplicações possam responder a necessidades variáveis de recursos da aplicação ao longo do tempo, a complexidade relacionada a uma arquitetura de software relacionada a serviços e a qualidade de serviço (QoS) envolvendo fatores como desempenho,(SOUSA et al, 2016).Dessas necessidades, a IBM produziu um manifesto em 2001 propondo o conceito de Computação Autonômica (CA), referente a sistemas computacionais capazes de autogerenciamento a partir de um conjunto de objetivos definidos(KHAN et al, 2018).Assim, tem-se que a computação autonômica objetiva o desenvolvimento de sistemas computacionais complexos capazes de autogerenciamento e adaptação a mudanças não previstas(SOUSA et al, 2016). mencionou que softwares e ambientes que tem dezenas de milhões de linhas de código de programação exigem profissionais cada vez mais capacitados para criar e gerenciar sistemas deixando-os em perfeito funcionamento.A necessidade de integrar vários ambientes tornando-os heterogêneos e redundantes vem tornando o trabalho desses profissionais cada vez mais difíceis de se controlar, manter, otimizar e gerenciar.…”

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O Ensino Da Matemática E Sua Contribuição Para O Desenvolvimento Da Consciência Ambiental Dos Estudantes Da Educação Básica

Liell¹,

Bayer²

2019

As Ciências Exatas E Da Terra No Século XXI

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A swarm solution for a cooperative and self-organized team of UAVs to search targets

Cited by 13 publications

References 18 publications

Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

Robot Swarm Navigation and Victim Detection Using Rendezvous Consensus in Search and Rescue Operations

O Ensino Da Matemática E Sua Contribuição Para O Desenvolvimento Da Consciência Ambiental Dos Estudantes Da Educação Básica

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