Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Trajectory Optimization for UAV-Aided Data Collections

  • Conference paper
  • First Online:
IoT as a Service (IoTaaS 2020)

Abstract

The application of the unmanned aerial vehicles (UAV) in future wireless networks is getting more and more popular. This article investigates the flight trajectory optimization problem with minimum energy consumption when the UAVs are communicating with the ground terminals (GT) for data collections. The specific flying speed is determined to minimize the energy consumption of the whole flying process. In addition, the algorithms to find the optimal trajectory are proposed. Experimental results are presented to show the effectiveness of our proposed algorithms.

This work was supported in part by the National Science Foundation of China (NSFC) with grant no. 61901534, in part by the Guangdong Basic and Applied Basic Research Foundation under Key Project 2019B1515120032, in part by the Science, Technology and Innovation Commission of Shenzhen Municipality with grant no. JCYJ20190807155617099. All authors equally contributed to this manuscript.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Ping, J.T.K., Ling, A.E., Quan, T.J., Dat, C.Y.: Generic unmanned aerial vehicle (UAV) for civilian application-A feasibility assessment and market survey on civilian application for aerial imaging. In: IEEE Conference (STUDENT), October 2012

    Google Scholar 

  2. Canetta, L., Mattei, G., Guanziroli, A.: Exploring commercial UAV market evolution from customer requirements elicitation to collaborative supply network management. In: IEEE International Conference (ICE), June 2017

    Google Scholar 

  3. Orfanus, D., de Freitas, E.P., Eliassen F.: Self-organization as a supporting paradigm for military UAV relay networks. IEEE Commun. Lett., 804–807 (April 2016)

    Google Scholar 

  4. Jessie, Y.C.: Chen: Effects of operator spatial ability on UAV-guided ground navigation. In: IEEE International Conference Human-Robet Interaction (HRI), March 2010

    Google Scholar 

  5. Zhang, Y.: Flight path planning of agriculture UAV based on improved artificial potential field method. In: IEEE 2018 Chinese Control and Decision Conference (CCDC), June 2018

    Google Scholar 

  6. Subba Rao, V.P., Srinivasa Rao, G.: Design and modelling of an affordable UAV based pesticide sprayer in agriculture applications. In: IEEE 2019 Fifth International Conference on Electrical Energy Systems (ICEES), February 2019

    Google Scholar 

  7. Zhang, Z., Li, C.: Application of unmanned aerial vehicle technology in modern agriculture. Agricultural Engineering, vol. 6 No.4, July 2016

    Google Scholar 

  8. Reshma, R., Ramesh, T.K., Sathish Kumar, P.: Security incident management in ground transportation system using UAVs. IEEE (ICCIC), December 2015

    Google Scholar 

  9. Reshma, R., Ramesh, T., Sathishkumar, P.: Security situational aware intelligent road traffic monitoring using UAVs. In: IEEE (VLSI-SATA), January 2016

    Google Scholar 

  10. Menouar, H., Guvenc, I., Akkaya, K., Selcuk Uluagac, A., Kadri, A., Tuncer, A.: UAV-enabled intelligent transportation systems for the smart city: applications and challenges. IEEE Commun., 22–28, March 2017

    Google Scholar 

  11. Wu, Q., Zeng, Y., Zhang, R.: Joint trajectory and communication design for multi-uav enabled wireless networks. IEEE Trans. Wireless Commun. 17(3), 2109–2121 (2018)

    Article  Google Scholar 

  12. Desset, C.: Flexible power modeling of lte base stations[J]. IEEE Wireless Commun. Netw. Conf. (WCNC) pp. 2858–2862 (Apr 2012)

    Google Scholar 

  13. Franco, C.D., Buttazzo, G.: Energy-aware coverage path planning of uavs. In: IEEE International on Autonomous Robot Systems and Competitions, pp. 111–117, April 2015

    Google Scholar 

  14. Greitzer, E.M., Spakovszky, Z.S., Waitz., I.A.: Thermodynamics and propulsion[OL]. MIT Course Notes, July 2016

    Google Scholar 

  15. Raja, M.A.Z.: Technology - Information Technology; Huaibei Normal University Reports Findings in Information Technology (Backtracking Search Optimization Algorithm Based On Knowledge Learning)

    Google Scholar 

  16. Sharma, H., Sebastian, T., Balamuralidhar, P.: An efficient backtracking-based approach to turn-constrained path planning for aerial mobile robots. In: 2017 European Conference on Mobile Robots (ECMR), Paris, 2017, pp. 1–8 (2017). https://doi.org/10.1109/ECMR.2017.8098712

  17. Chen, E., Sun, Y., Pan, Z., Liu, X.: Discrete particle swarm optimization with greedy randomized adaptive search procedure for linear order problem. In: 2010 Sixth International Conference on Natural Computation (ICNC 2010) (2010)

    Google Scholar 

  18. Dharan, S., Nair, A.S.: Biclustering of gene expression data using greedy randomized adaptive search procedure. In: TENCON 2008–2008 IEEE Region 10 Conference

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Congduan Li .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, H., Zhang, C., Zhang, Z., Zhou, C., Zhang, Y., Li, C. (2021). Trajectory Optimization for UAV-Aided Data Collections. In: Li, B., Li, C., Yang, M., Yan, Z., Zheng, J. (eds) IoT as a Service. IoTaaS 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 346. Springer, Cham. https://doi.org/10.1007/978-3-030-67514-1_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-67514-1_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67513-4

  • Online ISBN: 978-3-030-67514-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics