Name
Abstract | ||
|---|---|---|
Unmanned aerial vehicle technology has made great progress in the past and is widely used in many fields. However, they are unable to meet large-scale and complex missions with a limited energy reserve. Only multiple unmanned aerial vehicles (multi-UAV) work together to better cope with this problem and have been extensively studied. In this paper, a new systematic framework is proposed to solve the problem of multi-UAVcollaborative task allocation. It is formulated as a combinatorial optimization problem and solved by the improved clustering algorithm. The purpose is to enable multi-UAV to complete tasks with lower energy consumption. As the number of UAVs rises, it also appears the flight safety issues such as collisions among the UAVs, an improved multi-UAV collision-resistant method based on the improved artificial potential field is proposed. Besides, the UAVs connected with the internet are vulnerable to the various type of network attacks, a method based on the intrusion detection system is proposed to resist the network attack during multi-UAV mission execution. We have also proposed an improved method to improve the accuracy of task allocation further. In addition, an online real-time path planning is proposed to enhance the robustness of multi-UAV to cope with sudden problems. Finally, the numerical simulations and real physical flying experiments showed that the proposed method could provide a viable solution for multi-UAV task allocation; moreover, compared with other task allocation methods, our method has great performance. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2019.2902221 | IEEE ACCESS |
Keywords | Field | DocType |
Multi-UAV,task allocation,collusion-resistant,secure communication,intrusion detection system,clustering algorithm | Motion planning,Resource management,Task analysis,Computer science,Robustness (computer science),Cluster analysis,Intrusion detection system,Energy consumption,The Internet,Distributed computing | Journal |
Volume | ISSN | Citations |
7 | 2169-3536 | 1 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhangjie Fu | 1 | 405 | 19.78 |
| Yuanhang Mao | 2 | 1 | 0.68 |
| Daojing He | 3 | 1013 | 58.40 |
| Jingnan Yu | 4 | 7 | 1.06 |
| Guowu Xie | 5 | 155 | 7.03 |