Skip to main content
SpringerLink
Log in

Distributed Multi-agent Shepherding with Consensus

  • Conference paper
  • First Online:
Advances in Swarm Intelligence (ICSI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12690))

Included in the following conference series:

Abstract

The field of swarm guidance and control can rely on intrinsic strategies such as a rule-based system within each member of the swarm or extrinsic strategies, whereby an external agent guides the swarm. In the shepherding problem, sheepdogs drive and collect a flock (swarm) of sheep, guiding them to a goal location. In the case of multiple dogs guiding the swarm, we examine how shared contextual awareness of the sheepdog agents improves the performance when solving the shepherding problem. Specifically consensus around the dynamic centre of mass of a flock is shown to improve shepherding performance.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. Chen, C., Zhu, S., Guan, X., Shen, X.S.: Distributed consensus estimation of wireless sensor networks. Wireless Sensor Networks. SCS, pp. 5–11. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-12379-0_2

    Chapter  MATH  Google Scholar 

  2. El-Fiqi, H., et al.: The limits of reactive shepherding approaches for swarm guidance. IEEE Access 8, 214658–214671 (2020)

    Google Scholar 

  3. Elsayed, S., et al.: Path planning for shepherding a swarm in a cluttered environment using differential evolution. arXiv preprint arXiv:2008.12639 (2020)

  4. Fan, S., Sun, C., Yang, C., Ye, B.: Fast distributed kalman-consensus filtering algorithm with local feedback regulation. In: 2015 IEEE International Conference on Information and Automation, pp. 2345–2350. IEEE (2015)

    Google Scholar 

  5. Foh, C.H., Zukerman, M.: Performance analysis of the IEEE 802.11 mac protocol. In: Proceedings of European Wireless, vol. 2 (2002)

    Google Scholar 

  6. Ge, X., Han, Q.L.: Consensus of multiagent systems subject to partially accessible and overlapping markovian network topologies. IEEE Trans. Cybern. 47(8), 1807–1819 (2016)

    Article  Google Scholar 

  7. Harrison, J.F., Vo, C., Lien, J.-M.: Scalable and robust shepherding via deformable shapes. In: Boulic, R., Chrysanthou, Y., Komura, T. (eds.) MIG 2010. LNCS, vol. 6459, pp. 218–229. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16958-8_21

    Chapter  Google Scholar 

  8. Henderson, J., Zamani, M., Mahony, R., Trumpf, J.: A minimum energy filter for localisation of an unmanned aerial vehicle. arXiv preprint arXiv:2009.04630 (2020)

  9. Hocraffer, A., Nam, C.S.: A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management. Appl. Ergon. 58, 66–80 (2017)

    Article  Google Scholar 

  10. Li, W., Jia, Y., Du, J.: Distributed kalman consensus filter with intermittent observations. J. Franklin Inst. 352(9), 3764–3781 (2015)

    Article  MathSciNet  Google Scholar 

  11. Luo, X., Li, X., Li, S., Jiang, Z., Guan, X.: Flocking for multi-agent systems with optimally rigid topology based on information weighted kalman consensus filter. Int. J. Control Autom. Syst. 15(1), 138–148 (2017)

    Article  Google Scholar 

  12. Olfati-Saber, R., Murray, R.M.: Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Autom. Control 49(9), 1520–1533 (2004)

    Article  MathSciNet  Google Scholar 

  13. Schultz, A., Grefenstette, J.J., Adams, W.: Roboshepherd: learning a complex behavior. Robot. Manuf. Recent Trends Res. Appl. 6, 763–768 (1996)

    Google Scholar 

  14. Spanos, D.P., Olfati-Saber, R., Murray, R.M.: Dynamic consensus on mobile networks. In: IFAC World Congress, pp. 1–6. Citeseer (2005)

    Google Scholar 

  15. Ströombom, D., et al.: Solving the shepherding problem: heuristics for herding autonomous, interacting agents. J. R. Soc. Interface 11(100), 20140719 (2014)

    Google Scholar 

  16. Zamani, M., Hunjet, R.: Collaborative pose filtering using relative measurements and communications. In: 2019 12th Asian Control Conference (ASCC), pp. 919–924. IEEE (2019)

    Google Scholar 

  17. Zhi, J., Lien, J.M.: Learning to herd agents amongst obstacles: Training robust shepherding behaviors using deep reinforcement learning. arXiv preprint arXiv:2005.09476 (2020)

Download references

Author information

Authors and Affiliations

  1. Defence Science and Technolgy Group, Edinburgh, SA, 5111, Australia

    Benjamin Campbell & Robert Hunjet

  2. University of New South Wales, Canberra, ACT, 2612, Australia

    Heba El-Fiqi & Hussein Abbass

Authors
  1. Benjamin Campbell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heba El-Fiqi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Robert Hunjet
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hussein Abbass
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Benjamin Campbell .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Campbell, B., El-Fiqi, H., Hunjet, R., Abbass, H. (2021). Distributed Multi-agent Shepherding with Consensus. In: Tan, Y., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2021. Lecture Notes in Computer Science(), vol 12690. Springer, Cham. https://doi.org/10.1007/978-3-030-78811-7_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78811-7_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78810-0

  • Online ISBN: 978-3-030-78811-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation