A UAV-Collaborative Sensing Method for Efficient Monitoring of Disaster Sites

  • Akimitsu KanzakiEmail author
  • Hideyuki Akagi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 926)


In this paper, we propose a method that achieves efficient monitoring of the entire of a disaster site, using multiple UAVs (Unmanned Aerial Vehicles) owned by different organizations and individuals. In our proposed method, UAVs collaboratively operates by sharing information about UAVs operating in the target region via local direct wireless communication. Using information shared with other UAVs, each UAV sets its own moving path so as to move to areas where no UAVs have visited for a long time. In doing so, our proposed method enables to monitor the entire of a disaster site evenly and frequently. We confirmed the effectiveness of our proposed method through simulation experiments.



This research is supported by the Grants-in-Aid for Young Scientists (B)(17K12673) of Japan Society for the Promotion of Science, Japan, and the Cooperative Research Project of the RIEC, Tohoku University.


  1. 1.
    Cesare, K., Skeele, R., Yoo, S.H., Zhang, Y., Hollinger, G.: Multi-UAV explaration with limited communication and battery. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA 2015), pp. 2230–2235 (2015)Google Scholar
  2. 2.
    Chen, Y., Zhang, H., Xu, M.: The coverage problem in UAV network: a survey. In: Proceedings of the International Conference on Computing Communications and Networking Technologies (ICCCNT 2014), pp. 1–5 (2014)Google Scholar
  3. 3.
    Franco, C.D., Buttazzo, G.: Energy-aware coverage path planning of UAVs. In: Proceedings of the IEEE International Conference Autonomous Robot Systems and Competitions (ICARSC 2015), pp. 111–117 (2015)Google Scholar
  4. 4.
    Ghaffarkhah, A., Mostofi, Y.: Dynamic networked coverage of time-varying environments in the presence of fading communication channels. ACM Trans. Sens. Netw. 10(3), Article no. 45 (2014)Google Scholar
  5. 5.
    Maza, I., Ollero, A.: Multiple UAV cooperative searching operation using polygon area decomposition and efficient coverage algorithms. Distrub. Auton. Rob. Syst. 6, 221–230 (2007)CrossRefGoogle Scholar
  6. 6.
    Mirzaei, M., Sharifi, F., Gordon, B.W., Rabbath, C.A., Zhang, Y.M.: Cooperative multi-vehicle search and coverage problem in uncertain environments. In: Proceedings of the IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), pp. 4140–4145 (2011)Google Scholar
  7. 7.
    Rashed, S., Soyturk, M.: Analyzing the effects of UAV mobility patterns on data collection in wireless sensor networks. Sensors 17(2), 413 (2017)CrossRefGoogle Scholar
  8. 8.
    Sanchez-Garcia, J., Reina, D.G., Toral, S.L.: A distributed PSO-based exploration algorithm for a UAV network assisting a disaster scenario. Future Gener. Comput. Syst. 90, 129–148 (2019)CrossRefGoogle Scholar
  9. 9.
    Sharma, V., Kumar, R.: A cooperative network framework for multi-UAV guided ground ad hoc networks. J. Intell. Rob. Syst. 77(3–4), 629–652 (2015)CrossRefGoogle Scholar
  10. 10.
    Sujit, P.B., Lucani, D.E., Sousa, J.B.: Joint route planning for UAV and sensor network for data retrieval. In: Proceedings of the IEEE International Systems Conference (SysCon 2013), pp. 681–687 (2013)Google Scholar
  11. 11.
    Yin, C., Xiao, Z., Cao, X., Xi, X., Wang, P., Wu, D.: Offline and online search: UAV multi-objective path planning under dynamic urban environment. IEEE Internet of Things J. 99, 1 (2017)Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Science and Engineering, Academic AssemblyShimane UniversityMatsueJapan
  2. 2.People Software CorporationKurashikiJapan

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