Cooperative Threat Engagement Using Drone Swarms

Ricardo, Jorge A.; Giacomossi, Luiz; Trentin, João Francisco Silva; Brancalion, Jose F. B.; Máximo, Marcos R. O. A.; Santos, Davi Antônio dos

doi:10.1109/access.2023.3239817

Cited by 5 publications

(4 citation statements)

References 42 publications

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“…It is assumed in this study that drones will experience energy costs when selecting to wait for higher reward tasks. Therefore, drones will balance the benefits and costs for task planning [24][25][26]. Based on this, task informatization can be divided into two main stages: release and perception, as shown in Figure 2.…”

Section: Design Of Uav Task Allocation and Channel Security Spectrum ...mentioning

confidence: 99%

UAV Network Channel Allocation Method Based on Bipartite Graph Popular Matching Algorithm

Li,

Guo

2024

IEEE Access

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To address the challenges of selecting task schemes and ensuring secure channels duringdata collection and transmission by unmanned aerial vehicles, the study divides the secure transmission model into physical domain and social domain based on graph theory to ensure the security of unmanned aerial vehicles during task execution. Secondly, the multi to one matching problem was optimized through matching theory, achieving maximum benefits between drones and ground to ground (D2D) users. This study designed a stable matching scheme for drone task allocation based on bipartite graphs and a popular matching strategy for drone security spectrum resource allocation based on bipartite graphs. By adapting the design of a series of coherent actions of drones from information collection to information transmission, the efficiency and security of drone information transmission can be improved. The experimental results show that the average revenue of the designed algorithm for unmanned aerial vehicles is between 21 and 40, while the average revenue range for a single task is between 173 and 210. Compared with other algorithms in terms of security performance for drones and D2D users, the algorithm designed in the study shows strong advantages. Specifically, in terms of drone safety performance, the design algorithm's performance improves as the spectrum sharing limit increases. The advantage becomes more obvious when the sharing limit value reaches 1; From the perspective of D2D users, the average worst-case safety rate of the design algorithm increases with the increase of flight cycle and average power. Compared tofixed-trajectory drones, the overall performance gain of the research and design algorithm reaches about 18.2%, and compared with fixed power drones, the overall performance gain reaches about 15.5%. In summary, the research has made significant progress in task allocation and channel security spectrum resource allocation. The design algorithm achieves the optimal effect between computational complexity and performance, and overall maximizes the benefits between drones and D2D users.

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Section: Design Of Uav Task Allocation and Channel Security Spectrum ...mentioning

confidence: 99%

UAV Network Channel Allocation Method Based on Bipartite Graph Popular Matching Algorithm

Li,

Guo

2024

IEEE Access

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“…In intelligent transportation systems (ITS), one application of collective intelligence is platooning, which significantly reduces fuel consumption and provides a smooth traffic flow [7]. In drone systems, collective intelligence is used to establish drone swarming when performing certain goals, such as formation control [8], espionage [9], or defense mechanisms [10]. Moreover, collective intelligence is widely used in robotics applications to create multi-agent systems, in which robots perform collaborative actions to accomplish a certain mission [11].…”

Section: Introductionmentioning

confidence: 99%

Enhancing Optical Camera Communication Performance for Collaborative Communication Using Positioning Information

Utama,

Sitanggang,

Nasution

et al. 2024

IEEE Access

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Optical camera communication (OCC) has emerged as a promising alternative technology for radio frequency (RF)-based communication systems. However, existing OCC approaches only consider transmitting data through broadcasting, without any ability for point-to-point communication. In this paper, a new modulation scheme termed distance color-coded on-off keying (DCC-OOK) is proposed that uses distance information retrieved from relative localization. The proposed method allows OCC to perform pointto-point communication and facilitates bidirectional communication. An OCC system that uses multi-sensor fusion of a camera and LiDAR is considered, in which calibration of the sensors and LED array segmentation for performing relative localization between the OCC transmitter and the OCC receiver are explained. The results indicate that both point-to-point and bidirectional communication were achieved with the proposed OCC system. During implementation, the distance between transmitter and receiver was varied between 1.0 and 4.0 m, and the system demonstrated a maximum data rate of 38.4 kbps with a lowest BER of 0.03.

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“…With the changing societal landscape, there is a growing trend towards achieving optimal efficiency with minimal personnel. Therefore, utilizing unmanned aerial vehicles (UAVs) [2][3][4][5][6] and Internet of things (IoT) [7][8][9][10][11][12][13][14][15][16][17][18] technology to achieve costeffective disaster rescue operations has become a viable solution. With the continuous research and development of UAV technology, there is an increasing demand for UAV assistance in various fields.…”

Section: Introductionmentioning

confidence: 99%

“…With the continuous research and development of UAV technology, there is an increasing demand for UAV assistance in various fields. This includes search and rescue drones [2,3], transport drones [4], security drones [5], and service drones [6], among others. The concept of the IoT refers to the interconnection of physical devices and objects through the internet, enabling information sharing and intelligent interaction.…”

Section: Introductionmentioning

confidence: 99%

An unmanned aerial vehicle for search and rescue applications

Lai,

Yang

et al. 2023

J. Phys.: Conf. Ser.

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Unmanned aerial vehicles (UAVs) have emerged as potential tools for search and rescue. This study evaluates the feasibility of developing UAVs for search and rescue from multiple perspectives, including positioning and environmental monitoring considerations. The system architecture incorporates a UAV equipped with sensors for particulate matter, temperature/humidity, and carbon monoxide (CO) detection. Data collected by these sensors were compared with official data from the Environmental Protection Administration (EPA) in Taiwan to assess the reliability of the obtained results. The findings indicate that the data collected by the UAV closely align with the official data, suggesting their reliability and values as references. Furthermore, the study simulates the use of the UAV for automated flight route planning during disaster scenarios. The UAV efficiently navigates predetermined paths around disaster sites while monitoring environmental factors. The results highlight the importance of developing UAVs for search and rescue, as they integrate Internet of things (IoT) technology and provide geolocation and environmental information. The developed UAV enables the rapid acquisition of critical data, supporting decision-making and execution during rescue operations. This research provides a substantial demonstration of the UAV for search and rescue applications.

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Cooperative Threat Engagement Using Drone Swarms

Cited by 5 publications

References 42 publications

UAV Network Channel Allocation Method Based on Bipartite Graph Popular Matching Algorithm

UAV Network Channel Allocation Method Based on Bipartite Graph Popular Matching Algorithm

Enhancing Optical Camera Communication Performance for Collaborative Communication Using Positioning Information

An unmanned aerial vehicle for search and rescue applications

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