Abstract
Multi-AUV cooperative target search problem in unknown 3D underwater environment is not only a research hot spot but also a challenging task. To complete this task, each autonomous underwater vehicle (AUV) needs to move quickly without collision and cooperate with other AUVs to find the target. In this paper, an improved dolphin swarm algorithm- (DSA-) based approach is proposed, and the search problem is divided into three stages, namely, random cruise, dynamic alliance, and team search. In the proposed approach, the Levy flight method is used to provide a random walk for AUV to detect the target information in the random cruise stage. Then the self-organizing map (SOM) neural network is used to build dynamic alliances in real time. Finally, an improved DSA algorithm is presented to realize the team search. Furthermore, some simulations are conducted, and the results show that the proposed approach is capable of guiding multi-AUVs to achieve the target search task in unknown 3D underwater environment efficiently.
Highlights
Autonomous underwater vehicle (AUV) has a wide range of applications in the field of science, commerce, and military, such as searching missing airplanes and ships wreckage, maritime rescuing, and exploitation of marine resources [1,2,3,4]
The multi-AUV cooperative target search problem in unknown 3D underwater environment is studied. e technical details are not focused in this study, including the shape and movement of the AUV, environment detection, and communication problems. e search task in this paper is that an AUV system is used to find some targets in this underwater environment. e problems are introduced as follows: (1) e AUVs are labelled as ai, i 1, 2, . . . N, and the set of targets are denoted as ti, i 1, 2, . . . M
Conclusion e multi-AUV cooperative target search problem in unknown 3D underwater environment is studied in this paper, and a novel integrated method is proposed
Summary
Autonomous underwater vehicle (AUV) has a wide range of applications in the field of science, commerce, and military, such as searching missing airplanes and ships wreckage, maritime rescuing, and exploitation of marine resources [1,2,3,4]. The general cooperative search approaches for the ground mobile robot cannot be used directly for multi-AUVs. Much research has been done to deal with various tasks in the cooperative search task of multi-AUVs. For example, Zhu et al [16] proposed a biologically inspired selforganizing map method for the dynamic task assignment and path planning of multi-AUV system. Yi et al [18] studied the task assignment problem of a swarm of robots in 3D dynamic environments, and an improved approach that integrates the advantages and characteristics of biological neural systems is proposed.
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