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   SuSy-EnGaD: Surveillance System Enhanced by Games of DronesStolfi Rosso, Daniel  ; Brust, Mathias ; Danoy, Grégoire et alin Drones (2022), 6(13), In this article, we propose SuSy-EnGaD, a surveillance system enhanced by games of drones. We propose three different approaches to optimise a swarm of UAVs for improving intruder detection, two of them ... [more ▼] In this article, we propose SuSy-EnGaD, a surveillance system enhanced by games of drones. We propose three different approaches to optimise a swarm of UAVs for improving intruder detection, two of them featuring a multi-objective optimisation approach, while the third approach relates to the evolutionary game theory where three different strategies based on games are proposed. We test our system on four different case studies, analyse the results presented as Pareto fronts in terms of flying time and area coverage, and compare them with the single-objective optimisation results from games. Finally, an analysis of the UAVs trajectories is performed to help understand the results achieved. [less ▲] Detailed reference viewed: 41 (8 UL)Swarm-based counter UAV defense systemBrust, Matthias R. ; Danoy, Grégoire ; Stolfi Rosso, Daniel et alin Discover Internet of Things (2021), 1(1), Unmanned Aerial Vehicles (UAVs) have quickly become one of the promising Internet-of-Things (IoT) devices for smart cities. Thanks to their mobility, agility, and onboard sensors'customizability, UAVs ... [more ▼] Unmanned Aerial Vehicles (UAVs) have quickly become one of the promising Internet-of-Things (IoT) devices for smart cities. Thanks to their mobility, agility, and onboard sensors'customizability, UAVs have already demonstrated immense potential for numerous commercial applications. The UAVs expansion will come at the price of a dense, high-speed and dynamic traffic prone to UAVs going rogue or deployed with malicious intent. Counter UAV systems (C-UAS) are thus required to ensure their operations are safe. Existing C-UAS, which for the majority come from the military domain, lack scalability or induce collateral damages. This paper proposes a C-UAS able to intercept and escort intruders. It relies on an autonomous defense UAV swarm, capable of self-organizing their defense formation and to intercept the malicious UAV. This fully localized and GPS-free approach follows a modular design regarding the defense phases and it uses a newly developed balanced clustering to realize the intercept- and capture-formation. The resulting networked defense UAV swarm is resilient to communication losses. Finally, a prototype UAV simulator has been implemented. Through extensive simulations, we demonstrate the feasibility and performance of our approach. [less ▲] Detailed reference viewed: 65 (14 UL)UAV-UGV-UMV Multi-Swarms for Cooperative SurveillanceStolfi Rosso, Daniel ; Brust, Matthias R. ; Danoy, Grégoire et alin Frontiers in Robotics and AI (2021), 8 In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi ... [more ▼] In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi-Swarms). CROMM-MS is designed for controlling the trajectories of heterogeneous multi-swarms of aerial, ground and marine unmanned vehicles with important features such as prioritising early detections and success rate. A new Competitive Coevolutionary Genetic Algorithm (CompCGA) is proposed to optimise the vehicles’ parameters and escapers’ evasion ability using a predator-prey approach. Our results show that CROMM-MS is not only viable for surveillance tasks but also that its results are competitive in regard to the state-of-the-art approaches. [less ▲] Detailed reference viewed: 74 (5 UL) A Cooperative Coevolutionary Approach to Maximise Surveillance Coverage of UAV SwarmsStolfi Rosso, Daniel ; Brust, Matthias R. ; Danoy, Grégoire et alin IEEE 17th Annual Consumer Communications & Networking Conference CCNC 2020, Las Vegas, NV, USA, January 10-13, 2020 (2020) Detailed reference viewed: 124 (20 UL)Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary TechniquesStolfi Rosso, Daniel ; Brust, Matthias R. ; Danoy, Grégoire et alin Sensors (2020), 20(9), 2566 Detailed reference viewed: 146 (26 UL)Optimizing the Performance of an Unpredictable UAV Swarm for Intruder DetectionStolfi Rosso, Daniel ; Brust, Matthias R. ; Danoy, Grégoire et alin Optimization and Learning - Third International Conference, OLA 2020, Cádiz, Spain, February 17-19, 2020, Proceedings (2020) Detailed reference viewed: 153 (24 UL)Competitive Evolution of a UAV Swarm for Improving Intruder Detection RatesStolfi Rosso, Daniel ; Brust, Matthias R. ; Danoy, Grégoire et alin 2020 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020, New Orleans, LA, USA, May 18-22, 2020 (2020) Detailed reference viewed: 190 (21 UL) |
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