Cooperative Robots and Sensor Networks 2015

Koubâa, Anis; Dios, J.Ramiro Martnez-de

doi:10.1007/978-3-319-18299-5

Studies in Computational Intelligence

2015

DOI: 10.1007/978-3-319-18299-5

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Cooperative Robots and Sensor Networks 2015

Anis Koubâa¹,

J.Ramiro Martnez-de Dios²

Abstract: The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning th… Show more

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Cited by 9 publications

References 9 publications

(26 reference statements)

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DDS-Based Containment Control of Multiple UAV Systems

2020

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In this paper, we present a robust containment control design for multi Unmanned Aerial Vehicle Systems (UAVs) based on the Data Distribution Service (DDS) middleware and L 1 adaptive controller. The Data Distribution Service middleware, L 1 adaptive controller and graph theory technique are utilized for the navigation of the UAVs. The L 1 controller is utilized as a local controller for each UAVs and the graph theory approach is utilized to constitute the followers inside their leaders. Finally, the DDS Middleware is used to exchange data between the followers and their leaders. Robust adaptation of the L 1 controller makes the system robust with a high level of performance. Matlab simulation verified the robustness of the L 1 controller. We provide stability proofs using Lyapunov analysis for the UAVs framework.

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DDS-Based Containment Control of Multiple UAV Systems

2020

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A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments

Eledlebi

Hildmann

Ruta

et al. 2020

Drones

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Using autonomously operating mobile sensor nodes to form adaptive wireless sensor networks has great potential for monitoring applications in the real world. Especially in, e.g., disaster response scenarios—that is, when the environment is potentially unsafe and unknown—drones can offer fast access and provide crucial intelligence to rescue forces due the fact that they—unlike humans—are expendable and can operate in 3D space, often allowing them to ignore rubble and blocked passages. Among the practical issues faced are the optimizing of device–device communication, the deployment process and the limited power supply for the devices and the hardware they carry. To address these challenges a host of literature is available, proposing, e.g., the use of nature-inspired approaches. In this field, our own work (bio-inspired self-organizing network, BISON, which uses Voronoi tessellations) achieved promising results. In our previous approach the wireless sensors network (WSN) nodes were using knowledge about their coverage areas center of gravity, something which a drone would not automatically know. To address this, we augment BISON with a genetic algorithm (GA), which has the benefit of further improving network deployment time and overall coverage. Our evaluations show, unsurprisingly, an increase in energy cost. Two variations of our proposed GA-BISON deployment strategies are presented and compared, along with the impact of the GA. Counter-intuitively, performance and robustness increase in the presence of noise.

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A Multi-Agent System Using Decentralized Decision-Making Techniques for Area Surveillance and Intruder Monitoring

Patrinopoulou

Daramouskas

Meimetis

et al. 2022

Drones

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A decentralized swarm of quadcopters designed for monitoring an open area and detecting intruders is proposed. The system is designed to be scalable and robust. The most important aspect of the system is the swarm intelligent decision-making process that was developed. The rest of the algorithms essential for the system to be completed are also described. The designed algorithms were developed using ROS and tested with SITL simulations in the GAZEBO environment. The proposed approach was tested against two other similar surveilling swarms and one approach using static cameras. The addition of the real-time decision-making capability offers the swarm a clear advantage over similar systems, as depicted in the simulation results.

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Cooperative Robots and Sensor Networks 2015

Cited by 9 publications

References 9 publications

DDS-Based Containment Control of Multiple UAV Systems

DDS-Based Containment Control of Multiple UAV Systems

A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments

A Multi-Agent System Using Decentralized Decision-Making Techniques for Area Surveillance and Intruder Monitoring

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