Abstract
At present, multi-UUV formation cooperative full-area coverage search method multi-sampling “Z” shaped search path. The traditional “Z” shaped search path has the problem that all UUVs need to turn outside the search area during the search process, which greatly reduces the efficiency of the full-area coverage search. In this paper, an improved “Z-shaped” search path is proposed to solve this problem. Under the premise of ensuring complete coverage of the region, the method adaptively adjusts according to specific tasks, and selects the appropriate formation in real time according to the shape of the region, thus reducing the overall search path length of the UUV formation. Based on the improved Z-shaped search path, the sustainability of the search algorithm after formation reconstruction caused by faults is analyzed. The simulation results show that the improved algorithm can effectively improve the search efficiency of underwater vehicle formation compared with the traditional “Z” shaped search path.
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
References
Duan, J., Jiang, Z.: Joint scheduling optimization of a short-term hydrothermal power system based on an elite collaborative search algorithm. Energies 15(13), 4633 (2022)
Zheng, D., Liu, C., Huang, L.: Spatio-temporal coverage planning algorithm for multi-UAV and multi-sensor cooperative search. J. Phys: Conf. Ser. 2187(1), 012047 (2022)
Li, L., Zhang, X., Yue, W., Liu, Z.: Cooperative search for dynamic targets by multiple UAVs with communication data losses. ISA Trans. 114, 230–241 (2021)
Hou, K., Yang, Y., Yang, X., Lai, J.: Distributed cooperative search algorithm with task assignment and receding horizon predictive control for multiple unmanned aerial vehicles. IEEE Access 9, 6122–6136 (2021)
Sun, Z., Yen, G.G., Wu, J., Ren, H., An, H., Yang, J.: Mission planning for energy-efficient passive UAV radar imaging system based on substage division collaborative search. IEEE Trans. Cybern. 53, 275–288 (2021)
He, C., et al.: Accelerating large-scale multi-objective optimization via problem reformulation. IEEE Trans. Evol. Comput. 23(6), 949–961 (2019)
Lin, J., He, C., Cheng, R.: Adaptive dropout for high-dimensional expensive multiobjective optimization. Complex Intell. Syst. 8(1), 271–285 (2021). https://doi.org/10.1007/s40747-021-00362-5
Liang, H., Fu, Y., Kang, F., Gao, J., Qiang, N.: A behavior-driven coordination control framework for target hunting by UUV intelligent swarm. IEEE Access 8, 4838–4859 (2020)
Liu, Y., Wang, M., Su, Z., et al.: Multi-AUVs cooperative target search based on autonomous cooperative search learning algorithm. J. Marine Sci. Eng. 8(11), 843 (2020)
Ni, J., Tang, G., Mo, Z., Cao, W., Yang, S.X.: An improved potential game theory based method for Multi-UAV cooperative search. IEEE Access 8, 47787–47796 (2020)
Bo, L., et al.: Multi-UAV collaborative search and strike based on reinforcement learning. J. Phys. Conf. Ser. 1651(1), 012115 (2020)
Ma, X.W., Chen, Y.L., Bai, G.Q., Sha, Y.B., Liu, J.: Multi-autonomous underwater vehicles collaboratively search for intelligent targets in an unknown environment in the presence of interception. Proc. Inst. Mech. Eng. Part C: J. Mech. Eng. Sci. 235(9), 1539–1554 (2021)
Shao, Q., Jia, M., Xu, C., Zhu, Y.: Multi-helicopter collaborative search and rescue operation research based on decision-making. J. Supercomput. 76(5), 3231–3251 (2018). https://doi.org/10.1007/s11227-018-2555-7
Huang, P.Q., Wang, Y., Wang, K., Liu, Z.Z.: A bilevel optimization approach for joint offloading decision and resource allocation in cooperative mobile edge computing. IEEE Trans. Cybern. 50(10), 4228–4241 (2019)
Wenjun, D., et al.: Investigation on optimal path for submarine search by an unmanned underwater vehicle. Comput. Electr. Eng. 79(C), 106468 (2019)
Ziyang, Z., et al.: Distributed intelligent self-organized mission planning of multi-UAV for dynamic targets cooperative search-attack. Chin. J. Aeronaut. 32(12), 2706–2716 (2019)
John, G.B., Thomas, A.W.: A ROC-based approach for developing optimal strategies in UUV search planning. IEEE J. Oceanic Eng. 43(4), 843–855 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhang, S. (2023). Multi-UUV Formation Cooperative Full-Area Coverage Search Method. In: Pan, L., Zhao, D., Li, L., Lin, J. (eds) Bio-Inspired Computing: Theories and Applications. BIC-TA 2022. Communications in Computer and Information Science, vol 1801. Springer, Singapore. https://doi.org/10.1007/978-981-99-1549-1_35
Download citation
DOI: https://doi.org/10.1007/978-981-99-1549-1_35
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-1548-4
Online ISBN: 978-981-99-1549-1
eBook Packages: Computer ScienceComputer Science (R0)