Employing Multiple Unmanned Aerial Vehicles for Co-Operative Path Planning

被引:26
|
作者
Habib, Durdana [1 ]
Jamal, Habibullah [2 ]
Khan, Shoab A. [3 ]
机构
[1] Natl Univ Comp & Emerging Sci, Dept Elect Engn, Islamabad, Pakistan
[2] Univ Engn & Technol, Dept Elect Engn, Taxila, Pakistan
[3] Natl Univ Sci & Technol, Dept Comp Syst Engn, Rawalpindi, Pakistan
关键词
Multiple Depot Vehicle Routing Problem; Cooperative Path Planning; Optimal Resource Allocation; Mixed Integer Linear Programming; TRAVELING-SALESMAN PROBLEM; ENVIRONMENTS; FORMULATIONS; CONSTRAINTS; ROBOTS; UAVS;
D O I
10.5772/56286
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In this paper, we work to develop a path planning solution for a group of Unmanned Aerial Vehicles (UAVs) using a Mixed Integer Linear Programming (MILP) approach. Co-operation among team members not only helps reduce mission time, it makes the execution more robust in dynamic environments. However, the problem becomes more challenging as it requires optimal resource allocation and is NP-hard. Since UAVs may be lost or may suffer significant damage during the course of the mission, plans may need to be modified in real-time as the mission proceeds. Therefore, multiple UAVs have a better chance of completing a mission in the face of failures. Such military operations can be treated as a variant of the Multiple Depot Vehicle Routing Problem (MDVRP). The proposed solution must be such that m UAVs start from multiple source locations to visit n targets and return to a set of destination locations such that (1) each target is visited exactly by one of the chosen UAVs (2) the total distance travelled by the group is minimized and (3) the number of targets that each UAV visits may not be less than K or greater than L.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Parallel Algorithm for the Path Planning of Multiple Unmanned Aerial Vehicles
    Roberge, Vincent
    Tarbouchi, Mohammed
    [J]. 2020 FOURTH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING IN DATA SCIENCES (ICDS), 2020,
  • [2] Survey of Cooperative Path Planning for Multiple Unmanned Aerial Vehicles
    Cheng, Xiaoming
    Cao, Dong
    Li, Chuntao
    [J]. MECHANICAL COMPONENTS AND CONTROL ENGINEERING III, 2014, 668-669 : 388 - 393
  • [3] Path Planning for Multiple Unmanned Aerial Vehicles Using Genetic Algorithms
    Li, Howard
    Fu, Yi
    Elgazzar, Khalid
    Paull, Liam
    [J]. 2009 IEEE 22ND CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1 AND 2, 2009, : 913 - 916
  • [4] Ellipsoidal Path Planning for Unmanned Aerial Vehicles
    Villasenor, Carlos
    Gallegos, Alberto A.
    Lopez-Gonzalez, Gehova
    Gomez-Avila, Javier
    Hernandez-Barragan, Jesus
    Arana-Daniel, Nancy
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (17):
  • [5] Collaborative Path Planning for Multiple Unmanned Aerial Vehicles to Avoid Sudden Threats
    Chen, Xia
    Zhao, Miaoyan
    [J]. 2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 2196 - 2201
  • [6] An Algorithm for Path Planning of Multiple Unmanned Aerial Vehicles Based on Bezier Curve
    Hu Feng
    Wang Shuo
    [J]. PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE, 2010, : 3660 - 3665
  • [7] Velocity field path-planning for single and multiple unmanned aerial vehicles
    McInnes, CR
    [J]. AERONAUTICAL JOURNAL, 2003, 107 (1073): : 419 - 426
  • [8] Path Planning for Multiple Unmanned Aerial Vehicles by Parameterized Cornu-Spirals
    Dai, Ran
    Cochran, John E., Jr.
    [J]. 2009 AMERICAN CONTROL CONFERENCE, VOLS 1-9, 2009, : 2391 - +
  • [9] Path planning in unmanned aerial vehicles: An optimistic overview
    Shahid, Noor
    Abrar, Muhammad
    Ajmal, Ushna
    Masroor, Roha
    Amjad, Shehzad
    Jeelani, Mubashir
    [J]. INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2022, 35 (06)
  • [10] Survey on Coverage Path Planning with Unmanned Aerial Vehicles
    Cabreira, Taua M.
    Brisolara, Lisane B.
    Paulo R., Ferreira Jr.
    [J]. DRONES, 2019, 3 (01) : 1 - 38