Skip to main content

Quad-Rotor UAVs Experiments for Formation Flight

  • Conference paper
  • First Online:
Proceedings of 2021 Chinese Intelligent Systems Conference

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 805))

  • 1764 Accesses

Abstract

To achieve the experimental verification of our previous formation control algorithm, a formation flight platform based on quad-rotor unmanned aerial vehicles (UAVs) is designed with multi-process communication. A so-called Mission Planner, that is, an open-source UAV ground station program, is redesigned for leader-following formation flying. The experiments without horizontal rotation and with a virtual ground leader are discussed in details.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 449.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Na, H.J., Yoo, S.: PSO-based dynamic UAV positioning algorithm for sensing information acquisition in wireless sensor networks. IEEE Access 7, 77499–77513 (2019)

    Google Scholar 

  2. Yang, L., Yao, H., Wang, J., Jiang, C., Benslimane, A., Liu, Y.: Multi-UAV-enabled load-balance mobile-edge computing for IoT networks. IEEE Internet Things J. 7(8), 6898–6908 (2020)

    Google Scholar 

  3. Wang, Q., Dai, H., Wang, Q., Shukla, M.K., Zhang, W., Soares, C.G.: On connectivity of UAV-assisted data acquisition for underwater Internet of Things. IEEE Internet Things J. 7(6), 5371–5385 (2020)

    Google Scholar 

  4. Cao, H., Yao, H., Cheng, H., Lian, S.: A solution for data collection of large-scale outdoor Internet of Things based on UAV and dynamic clustering. In: 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), pp. 2133–2136 (2020)

    Google Scholar 

  5. Yi, M., Wang, X., Liu, J., Zhang, Y., Bai, B.: Deep reinforcement learning for fresh data collection in UAV-assisted IoT networks. In: IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 716–721 (2020)

    Google Scholar 

  6. Jia, Z., Qin, X., Wang, Z., Liu, B.: Age-based path planning and data acquisition in UAV-assisted IoT networks. In: 2019 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 1–6 (2019)

    Google Scholar 

  7. Ye, H., Kang, X., Joung, J., Liang, Y.: Optimization for full-duplex rotary-wing UAV-enabled wireless-powered IoT networks. IEEE Trans. Wirel. Communi. 19(7), 5057–5072 (2020)

    Google Scholar 

  8. Yu, T., Wang, X., Shami, A.: UAV-enabled spatial data sampling in large-scale IoT systems using denoising autoencoder neural network. IEEE Internet Things J. 6(2), 1856–1865 (2019)

    Google Scholar 

  9. Tian, G., Zhang, L., Bai, X., Wang, B.: Real-time dynamic track planning of multi-UAV formation based on improved artificial bee colony algorithm. In: 2018 37th Chinese Control Conference (CCC), pp. 10055–10060 (2018)

    Google Scholar 

  10. Bian, L., Sun, W., Sun, T.: Trajectory following and improved differential evolution solution for rapid forming of UAV formation. IEEE Access 7, 169599–169613 (2019)

    Google Scholar 

  11. Kada, B., Khalid, M., Shaikh, M.S.: Distributed cooperative control of autonomous multi-agent UAV systems using smooth control. J. Syst. Eng. Electron. 31(6), 1297–1307 (2020)

    Google Scholar 

  12. Hentati, A.I., Krichen, L., Fourati, M., Fourati, L.C.: Simulation tools, environments and frameworks for UAV systems performance analysis. In: 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC), pp. 1495–1500 (2018)

    Google Scholar 

  13. del Arco, J.C., Alejo, D., Arrue, B.C., Cobano, J.A., Heredia, G., Ollero, A.: Multi-UAV ground control station for gliding aircraft. In: 2015 23rd Mediterranean Conference on Control and Automation (MED), pp. 36–43 (2015)

    Google Scholar 

  14. Aljehani, M., Inoue, M.: A swarm of computational clouds as multiple ground control stations of multi-UAV. In: 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE), pp. 1–2 (2017)

    Google Scholar 

  15. Han, B., Hu, C., Zhou, Y.: The ground station design for swarm unmanned aerial vehicle control. In: 2019 Chinese Control Conference (CCC), pp. 8248–8253 (2019)

    Google Scholar 

  16. Sun, Y., Li, L., Xue, K., Li, X., Liang, W., Han, Z.: Inhomogeneous multi-UAV aerial base stations deployment: a mean-field-type game approach. In: 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), pp. 1204–1208 (2019)

    Google Scholar 

  17. Jia, Q.Y., Wang, L.: Leader-follower flocking of multiple robotic fish. IEEE/ASME Trans. Mechatron. 20(3), 1372–1383 (2015)

    Google Scholar 

  18. Gu, D., Wang, Z.: Leader-follower flocking: algorithms and experiments. IEEE Trans. Control Syst. Technol. 17(5), 1211–1219 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yang-Yang Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, H., Chen, YY. (2022). Quad-Rotor UAVs Experiments for Formation Flight. In: Jia, Y., Zhang, W., Fu, Y., Yu, Z., Zheng, S. (eds) Proceedings of 2021 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 805. Springer, Singapore. https://doi.org/10.1007/978-981-16-6320-8_8

Download citation

Publish with us

Policies and ethics