Abstract
A search method for uncertain targets using multiple autonomous underwater vehicles (AUVs) is studied. To improve search efficiency, a cooperative search method based on target clustering and path optimization is proposed to reduce reactive consumption and obtain more revenue. Firstly, all the target grids are connected and the target areas are clustered according to the theory of minimum spanning tree. Secondly, the moving paths of AUVs are studied and divided into two stages: transferring to a target area and detecting in a target grid. And both of the stages are then optimized. Finally, a series of experiments in different cases are carried out, and the cooperative search method through target clustering and path optimization is compared with another two algorithms. Results show that the cooperative search method proposed in this paper can obtain a larger amount of total revenue in the same period of time with more stable performance than the other algorithms. It is proved that this method conduces to a more thorough search of the target areas.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baum ML, Passino KM (2002) A search theoretic approach to cooperative control for uninhabited air vehicle. In: AIAA-2002-4589
Chen L, You ZJ, Yang WJ (2008) Military information dictionary. PLA press, Beijing
Chen P, Hu JG, Yin ZW (2013) Quasi-optimal method for multiple UUVs cooperate to search static target. Fire Control Command Control 38:53–56
Das B, Subudhi B, Pati BB (2016) Cooperative formation control of autonomous underwater vehicles: an overview. Int J Autom Comput 13:199–225
Erignac CA (2007) An exhaustive swarming search strategy based on distributed pheromone maps. In: AIAA-2007-2822
Lum CW, Rysdy RT, Pongpunwattana A (2006) Occupancy based map searching using heterogeneous teams of autonomous vehicles. In: AIAA-2006-6196
Meng W, He Z, Su R et al (2017) Decentralized multi-UAV flight autonomy for moving convoys search and track. IEEE Trans Control Syst Technol 25:1480–1487
Ren W, Beard RW (2014) Distributed consensus in multi-vehicle cooperative control: theory and application. Publishing House of Electronics Industry, Beijing
Shen LC, Niu YF, Zhu HY (2013) Theories and methods of autonomous cooperative control for multiple UAVs. National Defense Industry Press, Beijing
Stone LD (2004) Theory of optimal search. Academic Press, New York
Wang Y, Zhang MX, Zheng YJ (2017) A hyper-heuristic method for UAV search planning. In: 8th international conference on swarm intelligence, ICSI2017, proceedings, pp. 454–464
Yan MQ, Liu B (2013) Multiple UAVs cooperative search strategy based on fuzzy C-mean cluster. Tactical Missile Technol 34:55–63
Zhu T, He WX, Ling HF, Zhang ZL (2018) Cooperative search strategies of multiple UAVs based on clustering using minimum spanning tree. In: 9th international conference on swarm intelligence, ICSI2018, proceedings, pp 112–121
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ling, H., Zhu, T., He, W. et al. Cooperative search method for multiple AUVs based on target clustering and path optimization. Nat Comput 20, 3–10 (2021). https://doi.org/10.1007/s11047-019-09749-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11047-019-09749-3