Name
Title | ||
|---|---|---|
Cooperative Search Method For Multiple Auvs Based On Target Clustering And Path Optimization |
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/s11047-019-09749-3 | NATURAL COMPUTING |
Keywords | DocType | Volume |
AUV, Cooperative search, Clustering, Path optimization | Journal | 20 |
Issue | ISSN | Citations |
1 | 1567-7818 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ling Haifeng | 1 | 4 | 2.42 |
| Tao Zhu | 2 | 82 | 14.36 |
| Weixiong He | 3 | 0 | 0.34 |
| Zhanliang Zhang | 4 | 2 | 1.38 |
| Hongchuan Luo | 5 | 0 | 0.68 |