Abstract
In order to improve the ability of unmanned aerial vehicle(UAV) cluster collaborative search and obstacle avoidance, a multi-UAV collaborative search method based on dynamic parameter adjustment is proposed. Firstly, based on the distributed model predictive control (DMPC) model, a collaborative search problem model is designed considering the rapidity of target discovery, the rapidity of covering the task area and the obstacle avoidance between drones. Secondly, the jump grid decision method not only expands the feasible solution of the search decision, but also ensures that the UAV can track the navigation point of the decision smoothly. At last, a dynamic adjustment method of search parameters is proposed, which realizes threat avoidance in collaborative search process by adjusting search parameters online. The simulation results show that the cluster cooperative search method based on dynamic parameter adjustment can fully consider the maneuverability of UAVs and realize threat avoidance during cooperative search, and improve the robustness of the algorithm after some nodes are damaged.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Deng, Y., Jiang, X.: Four-rotor UAV track planning algorithm based on improved artificial. Transducer Micro-Syst. Technol. 40(7), 130–133 (2021)
Yao, P., Wei, X.: Multi-UAV information fusion and cooperative trajectory optimization in target search. IEEE Syst. J. 16(3), 4325–4333 (2022)
Deng, Q. Research on multi-UAV collaborative mission planning technology. Supervisor: Wang Ningfei; YU Cambridge. Beijing Institute of Technology (2014)
Wang, H., Tian, J., Wei, L., et al.: Multi-UAV Cooperative search and tracking strategy with multiple moving Targets. Control Theory Appl. 38(07), 971–978 (2019)
Shao, R.: Research on dynamic task planning method of unmanned aerial vehicle cluster autonomous detection. Electronic Research Institute, China Electronics Technology Group Company (2022). https://doi.org/10.27728/dcnki.GDZKX.2022.000156
Zhao, X., Li, Z.: Multi-UAV Multi-dimensional decision-making collaborative Area Search based on DMPC. Modern Inform. Technol. 7(11), 15-20+25. (2019)
Trodden, P., Richards, A.: Multi-vehicle cooperative search using distributed model predictive control. AIAA Guidance, Navigation and Control Conference and Exhibit. Honolulu: AIAA, pp. 1–11 (2008)
Wang, N., Li, Z., Liang, X., et al.: The unmanned aerial vehicle (UAV) cooperative search cluster algorithm based on search intention interaction. J. Beijing Univ. Aeronaut. Astronaut. 13(3), 454–463 (2022). https://doi.org/10.13700/j.bh.1001-5965.2020.0602
Liu, Z.: Research on Collaborative Decision Making and Control Method of Multiple UAVs Under Restricted Communication. Northwestern Polytechnical University (2019). https://doi.org/10.27406/dcnki.Gxbgu.2019.000038
Zhao, F., Li, Z., Liang, X., et al.: Collaborative search of UAV cluster with limited communication bandwidth. Electro-optics Control 29(10), 12–17+23 (2012). (in Chinese)
Acknowledgments
This article is supported by the Defense Industrial Technology Development Program under No. JCKY2021204B051.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Si, J., Hao, M., Liu, Z. (2024). Cluster Collaborative Search Method Based on Dynamic Adjustment of Parameters. In: Li, X., Song, X., Zhou, Y. (eds) Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control. CCSICC 2023. Lecture Notes in Electrical Engineering, vol 1207. Springer, Singapore. https://doi.org/10.1007/978-981-97-3336-1_18
Download citation
DOI: https://doi.org/10.1007/978-981-97-3336-1_18
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-97-3335-4
Online ISBN: 978-981-97-3336-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)