Have a personal or library account? Click to login
Hierarchical Model for an AUV Swarm with a Leader Cover

Hierarchical Model for an AUV Swarm with a Leader

Open Access
|Mar 2025

References

  1. Bogue R. Underwater robots: A review of technologies and applications. Industrial Robot: An International Journal 42(3), 186–191, 2015, https://doi.org/10.1108/IR-01-2015-0010.
  2. Neira J, Sequeiros C, Huamani R, et al. Review on unmanned underwater robotics, structure designs, materials, sensors, actuators, and navigation control. Journal of Robotics 2021(1), 5542920, 2021, https://doi.org/10.1155/2021/5542920.
  3. Hasan K, Ahmad S, Liaf A F, et al. Oceanic challenges to technological solutions: A review of autonomous underwater vehicle path technologies in biomimicry, control, navigation and sensing. IEEE Access, 2024, https://doi.org/10.1109/ACCESS.2024.3380458.
  4. Luvisutto A, Al Shehhi A, Mankovskii N, et al. Robotic swarm for marine and submarine missions: Challenges and perspectives. In 2022 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV). IEEE, 2022, 1–8, https://doi.org/10.1109/AUV53081.2022.9965934.
  5. Gao Z, Shi Q, Fukuda T, et al. An overview of biomimetic robots with animal behaviors. Neurocomputing 332, 339–350, 2019, https://doi.org/10.1016/j.neucom.2018.12.071.
  6. Wang R, Du J, Xiong Z, et al. Hierarchical collaborative navigation method for UAV swarm. Journal of Aerospace Engineering 34(1), 04020097, 2021, https://doi.org/10.1061/(ASCE)AS.1943-5525.0001216.
  7. Liu X, Yan C, Zhou H, et al. Towards flocking navigation and obstacle avoidance for multi-UAV systems through hierarchical weighting Vicsek model. Aerospace 8(10), 286, 2021, https://doi.org/10.3390/aerospace8100286.
  8. Wang F, Chen Y. A novel hierarchical flocking control framework for connected and automated vehicles. IEEE Transactions on Intelligent Transportation Systems 22(8), 4801–4812, 2020, https://doi.org/10.1109/TITS.2020.2986436.
  9. Rehman F U, Thomas G, Anderlini E. Centralized control system design for underwater transportation using two hovering autonomous underwater vehicles (HAUVs). IFACPapersOnLine 52(11), 13–18, 2019, https://doi.org/10.1016/j.ifacol.2019.09.111.
  10. Zhao R, Miao M, Lu J, et al. Formation control of multiple underwater robots based on ADMM distributed model predictive control. Ocean Engineering 257, 111585, 2022, https://doi.org/10.1016/j.oceaneng.2022.111585.
  11. Quattrini Li A, Carver C J, Shao Q, et al. Communication for underwater robots: Recent trends. Current Robotics Reports 4(2), 13–22, 2023, https://doi.org/10.1007/s43154-023-00100-4.
  12. Antonelli G. Interconnected dynamic systems: An overview on distributed control. IEEE Control Systems Magazine 33(1), 76–88, 2013, https://doi.org/10.1109/MCS.2012.2225929.
  13. Huy D Q, Sadjoli N, Azam A B, et al. Object perception in underwater environments: A survey on sensors and sensing methodologies. Ocean Engineering 267, 113202, 2023, https://doi.org/10.1016/j.oceaneng.2022.113202.
  14. Vicsek T, Czirók A, Ben-Jacob E, et al. Novel type of phase transition in a system of self-driven particles. Physical Review Letters 75(6), 1226–1229, 1995, https://doi.org/10.1103/PhysRevLett.75.1226.
  15. Jia Y, Vicsek T. Modelling hierarchical flocking. New Journal of Physics 21(9), 093048, 2019, https://doi.org/10.1088/1367-2630/ab428e.
  16. Kim J. Leader-based flocking of multiple swarm robots in underwater environments. Sensors 23(11), 5305, 2023, https://doi.org/10.3390/s23115305.
  17. Zhao Q, Luan Y, Li S, et al. The influences of self-introspection and credit evaluation on self-organized flocking. Applied Sciences 13(18), 10361, 2023, https://doi.org/10.3390/app131810361.
  18. Jia Y, Wang L. Leader–follower flocking of multiple robotic fish. IEEE/ASME Transactions on Mechatronics 20(3), 1372–1383, 2015, https://doi.org/10.1109/TMECH.2014.2337375.
  19. Shen J. Cucker–Smale flocking under hierarchical leadership. SIAM Journal on Applied Mathematics 68(3), 694–719, 2008, https://doi.org/10.1137/060673254.
  20. Han W, Wang J, Wang Y, et al. Multi-UAV flocking control with a hierarchical collective behavior pattern inspired by sheep. IEEE Transactions on Aerospace and Electronic Systems, 2024, https://doi.org/10.1109/TAES.2024.3351961.
  21. Cai W, Liu Z, Zhang M, et al. Cooperative artificial intelligence for underwater robotic swarm. Robotics and Autonomous Systems 164, 104410, 2023, https://doi.org/10.1016/j.robot.2023.104410.
  22. Zhao Q, Li S, Wang G, et al. A local consistency algorithm to shorten the convergence time and improve the robustness of self-propelled swarms. In 2020 Chinese Automation Congress (CAC). IEEE, 2020, 4153–4157, https://doi.org/10.1109/CAC51589.2020.9327201.
  23. Tiwari R, Jain P, Butail S, et al. Effect of leader placement on robotic swarm control. Proceedings of the 16th Conference on Autonomous Agents and Multiagent Systems, 2017, 1387–1394, https://dl.acm.org/citation.cfm?id=3091316&CFID=840116400&CFTOKEN=63016478.
DOI: https://doi.org/10.2478/pomr-2025-0007 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585
Language: English
Page range: 71 - 80
Published on: Mar 5, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Qiang Zhao, Tengfei Yang, Guoqiang Tang, Yan Yang, Yu Luan, Gang Wang, Teng Wan, Minyi Xu, Shuai Li, Guangming Xie, published by Gdansk University of Technology
This work is licensed under the Creative Commons Attribution 4.0 License.