Enhancing Resolution and Fault Tolerance of Barrier Coverage with Unmanned Aerial Vehicles

被引:0
|
作者
Kumar, Amit [1 ]
Ghose, Debasish [2 ,3 ]
机构
[1] Indian Inst Sci, Robert Bosch Ctr Cyber Phys Syst, Bangalore 560012, India
[2] Indian Inst Sci, RBCCPS, Bangalore 560012, India
[3] Indian Inst Sci, Dept Aerosp Engn, Bangalore, Karnataka, India
来源
关键词
Unmanned Aerial Vehicle; Sensors; Optimization Algorithm; Search Algorithm; Computer Vision; sensor networks; Camera Sensor Networks; Barrier Coverage; Constraint optimization; Sensor coverage;
D O I
10.2514/1.I011298
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Securing the borders of a protected region using sensor network deployment is termed "barrier coverage." Unmanned aerial vehicles (UAVs) with cameras pointed downward can serve as mobile sensors to achieve barrier coverage of a protected region. The resolution of the camera, in addition to the extent of coverage, is a crucial parameter used to evaluate the quality of barrier coverage of a region. This paper presents a cost function that measures the resolution of a barrier coverage network, which can be used to improve the quality of an already established barrier-covered network. An optimization problem is proposed to find the barrier coverage while adhering to an overlapping constraint for UAVs that are placed arbitrarily in the belt. The approach is also demonstrated to be applicable for borders of any shape by utilizing multiple rectangular belts in combination. Furthermore, a fault tolerance model is proposed to ensure continuous barrier coverage even in the presence of faulty UAVs. This model utilizes nearby functional UAVs to compensate for any gaps and preserve the overlap constraint. Specifically, the model identifies neighboring functional UAVs for each faulty UAV and uses them to maintain barrier coverage.
引用
下载
收藏
页码:461 / 473
页数:13
相关论文
共 50 条
  • [21] Cooperative Unmanned Aerial and Surface Vehicles for Extended Coverage in Maritime Environments
    Santos, Matheus C.
    Bartlett, Ben
    Schneider, Vincent E.
    Bradaigh, Fiachra O.
    Blanck, Benjamin
    Santos, Phillipe C.
    Trslic, Petar
    Riordan, James
    Dooly, Gerard
    IEEE ACCESS, 2024, 12 : 9206 - 9219
  • [22] Distributed Control of Networked Unmanned Aerial Vehicles for Valley Area Coverage
    Shi, Mengji
    Qin, Kaiyu
    MOBILE INFORMATION SYSTEMS, 2016, 2016
  • [23] Coverage of an Environment Using Energy-Constrained Unmanned Aerial Vehicles
    Yu, Kevin
    O'Kane, Jason M.
    Tokekar, Pratap
    2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2019, : 3259 - 3265
  • [24] Efficient Deployment of Connected Unmanned Aerial Vehicles for Optimal Target Coverage
    Caillouet, Christelle
    Razafindralambo, Tahiry
    2017 GLOBAL INFORMATION INFRASTRUCTURE AND NETWORKING SYMPOSIUM (GIIS), 2017, : 1 - 8
  • [25] Unmanned aerial vehicles
    Scarpa, F
    AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, 2001, 73 (04): : 401 - 402
  • [26] Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage
    Mozaffari, Mohammad
    Saad, Walid
    Bennis, Mehdi
    Debbah, Merouane
    IEEE COMMUNICATIONS LETTERS, 2016, 20 (08) : 1647 - 1650
  • [27] A statistical area coverage model for unmanned aerial vehicles as relay platforms
    Zhu, Q. (zhuqiuming@nuaa.edu.cn), 1600, Chinese Society of Astronautics (35):
  • [28] On the Use of Unmanned Aerial Vehicles for Antenna and Coverage Diagnostics in Mobile Networks
    Garcia Fernandez, Maria
    Alvarez Lopez, Yuri
    Las-Heras Andres, Fernando
    IEEE COMMUNICATIONS MAGAZINE, 2018, 56 (07) : 72 - 78
  • [29] Unmanned aerial vehicles
    Braatz, Richard D.
    IEEE Control Systems, 2012, 32 (05) : 8 - 9
  • [30] Unmanned aerial vehicles
    Aerospace Engineering (Warrendale, Pennsylvania), 1994, 14 (03):