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Unmanned Aerial Vehicle (UAV) Cooperative Mission Planning

Received: 27 March 2017    Accepted: 12 April 2017    Published: 24 October 2017
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Abstract

Unmanned Aerial Vehicle (UAV) is a kind of new operational platform possessing ability to flight autonomously and perform independently a task,which can not only carry out non-attack tasks,such as military reconnaissance, surveillance and search, but also to carry out tasks to air-to-ground attacking, target bombing and so on. With the rapid development of UAVtechnology, more and more UAV will be applied in the future battlefield. An UAV combat troops have seven UAV bases, which are from P01 to P07. Every base has some FY-1 type UAVs. At the same time, FY-1 UAV can be loaded by two kinds of load, which are S-1 and S-2. Now we need to achieve the aim to detect 10 target groupsfromA01 to A10, which are total 68 goals. And each target group has radar station. Under the above condition, this papermakes the best plan for the UAV combat troops, and uses FY-1 UAV to find best route and scheduling strategy of UAV, which including each UAV drone off base, loading, departure time, track and target reconnaissance. The goal is to ensure minimum time summation in a effective probe range to stay defense radar for UAV. First of all, this paper considers only four UAV bases with FY-1 UAV, so the 68 targets are divided into four regions by K-means algorithm; Then the global shortest path model is established, when the local route is the shortest. The route is drawn according to the route. According to the former route, the general shortest path model is established. It is composed of shortest route distance and the distance from UAV to the corresponding area. And then this paper determine which base the UAV will go to. Finally, the minimum time is calculated as 17.52h. The eight UAVs are arranged in this process, which are composed of four UAVs withS-1 and fourUAVs withS-2. The UAVs are offered by P01, P03, P05 and P07.

Published in American Journal of Engineering and Technology Management (Volume 2, Issue 4)
DOI 10.11648/j.ajetm.20170204.11
Page(s) 36-44
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Multi UAV Cooperative, Task Planning, K-Means Algorithm, Dynamic Time Window

References
[1] D. C. L. Kristen Boon, "Warrant Requirement and Suspicion less Drone Searches," in The Domestic Use of Unmanned Aerial Vehicles, USA, Oxford University Press, 2014, p. 228.
[2] Chen Y B, Luo G C, Mei Y S, et al. UAV path planning using artificial potential field method updated by optimal control theory[J]. International Journal of Systems Science, 2014:1-14.
[3] Ye Yuanyuan. Multi UCAV cooperative task planing method. Doctoral dissertation research. National defense science and Technology University Changsha: National University of Defense Technology, 2015.
[4] Xia Jie. Real time flight path planning to meet the requirements of battlefield [J] Journal of Beihang University, 2014,30 (2): 95-99.
[5] Yang Zun. A monitoring route planning method for unmanned aerial vehicles [J]. tactical missile technology, 2011, (4): 63-67.
[6] Hu Zhonghua. Research and development of UAV mission planning system [J] aerospace electronic warfare, 2009,25 (4): 49-51.
[7] Gong Mao Guo, Wang Shuang, Ma Meng, et al. Two stage clustering algorithm for complex distributed data [J]. Journal of software, 2011,22 (11): 2760-2772.
[8] Fu Xiaowei. UCAV path planning algorithm. Research doctorate dissertation. Xi'an: Northwestern Polytechnical University, 2007.
[9] Roberge V, Tarbouchi M, Labonte G. Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAVPath Planning [J]. IEEE Transactions on Industrial Informatics, 2013, 9(1):132-141.
[10] S. Al-Hasan, G. Vachtsevanos. Intelligent Route Planning for Fast Autonomous Vehicles Operatingina Large natural Terrain [J]. Robotics and Autonomous Systems, 2014, 40:1-24.
[11] Changwen Zheng, Lei Li, Fanjiang Xu. Evolutionary Route Planner for Unmanned Air Vehicles [J]. IEEE Transactions on Robotics, 2015, 21(4): 609-620.
[12] Sonia Waharte, Niki Trigoni, Supporting Search and Rescure Operations with UAVs [J]. 2010 International Conference on Emerging Security Technologies, 2010, 2:142-147.
Cite This Article
  • APA Style

    Le Yu, Qian Liu. (2017). Unmanned Aerial Vehicle (UAV) Cooperative Mission Planning. American Journal of Engineering and Technology Management, 2(4), 36-44. https://doi.org/10.11648/j.ajetm.20170204.11

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    ACS Style

    Le Yu; Qian Liu. Unmanned Aerial Vehicle (UAV) Cooperative Mission Planning. Am. J. Eng. Technol. Manag. 2017, 2(4), 36-44. doi: 10.11648/j.ajetm.20170204.11

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    AMA Style

    Le Yu, Qian Liu. Unmanned Aerial Vehicle (UAV) Cooperative Mission Planning. Am J Eng Technol Manag. 2017;2(4):36-44. doi: 10.11648/j.ajetm.20170204.11

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  • @article{10.11648/j.ajetm.20170204.11,
      author = {Le Yu and Qian Liu},
      title = {Unmanned Aerial Vehicle (UAV) Cooperative Mission Planning},
      journal = {American Journal of Engineering and Technology Management},
      volume = {2},
      number = {4},
      pages = {36-44},
      doi = {10.11648/j.ajetm.20170204.11},
      url = {https://doi.org/10.11648/j.ajetm.20170204.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajetm.20170204.11},
      abstract = {Unmanned Aerial Vehicle (UAV) is a kind of new operational platform possessing ability to flight autonomously and perform independently a task,which can not only carry out non-attack tasks,such as military reconnaissance, surveillance and search, but also to carry out tasks to air-to-ground attacking, target bombing and so on. With the rapid development of UAVtechnology, more and more UAV will be applied in the future battlefield. An UAV combat troops have seven UAV bases, which are from P01 to P07. Every base has some FY-1 type UAVs. At the same time, FY-1 UAV can be loaded by two kinds of load, which are S-1 and S-2. Now we need to achieve the aim to detect 10 target groupsfromA01 to A10, which are total 68 goals. And each target group has radar station. Under the above condition, this papermakes the best plan for the UAV combat troops, and uses FY-1 UAV to find best route and scheduling strategy of UAV, which including each UAV drone off base, loading, departure time, track and target reconnaissance. The goal is to ensure minimum time summation in a effective probe range to stay defense radar for UAV. First of all, this paper considers only four UAV bases with FY-1 UAV, so the 68 targets are divided into four regions by K-means algorithm; Then the global shortest path model is established, when the local route is the shortest. The route is drawn according to the route. According to the former route, the general shortest path model is established. It is composed of shortest route distance and the distance from UAV to the corresponding area. And then this paper determine which base the UAV will go to. Finally, the minimum time is calculated as 17.52h. The eight UAVs are arranged in this process, which are composed of four UAVs withS-1 and fourUAVs withS-2. The UAVs are offered by P01, P03, P05 and P07.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Unmanned Aerial Vehicle (UAV) Cooperative Mission Planning
    AU  - Le Yu
    AU  - Qian Liu
    Y1  - 2017/10/24
    PY  - 2017
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    DO  - 10.11648/j.ajetm.20170204.11
    T2  - American Journal of Engineering and Technology Management
    JF  - American Journal of Engineering and Technology Management
    JO  - American Journal of Engineering and Technology Management
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    PB  - Science Publishing Group
    SN  - 2575-1441
    UR  - https://doi.org/10.11648/j.ajetm.20170204.11
    AB  - Unmanned Aerial Vehicle (UAV) is a kind of new operational platform possessing ability to flight autonomously and perform independently a task,which can not only carry out non-attack tasks,such as military reconnaissance, surveillance and search, but also to carry out tasks to air-to-ground attacking, target bombing and so on. With the rapid development of UAVtechnology, more and more UAV will be applied in the future battlefield. An UAV combat troops have seven UAV bases, which are from P01 to P07. Every base has some FY-1 type UAVs. At the same time, FY-1 UAV can be loaded by two kinds of load, which are S-1 and S-2. Now we need to achieve the aim to detect 10 target groupsfromA01 to A10, which are total 68 goals. And each target group has radar station. Under the above condition, this papermakes the best plan for the UAV combat troops, and uses FY-1 UAV to find best route and scheduling strategy of UAV, which including each UAV drone off base, loading, departure time, track and target reconnaissance. The goal is to ensure minimum time summation in a effective probe range to stay defense radar for UAV. First of all, this paper considers only four UAV bases with FY-1 UAV, so the 68 targets are divided into four regions by K-means algorithm; Then the global shortest path model is established, when the local route is the shortest. The route is drawn according to the route. According to the former route, the general shortest path model is established. It is composed of shortest route distance and the distance from UAV to the corresponding area. And then this paper determine which base the UAV will go to. Finally, the minimum time is calculated as 17.52h. The eight UAVs are arranged in this process, which are composed of four UAVs withS-1 and fourUAVs withS-2. The UAVs are offered by P01, P03, P05 and P07.
    VL  - 2
    IS  - 4
    ER  - 

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Author Information
  • Graduate Department, Beijing WuZi University, Beijing, China

  • Graduate Department, Beijing WuZi University, Beijing, China

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