Task allocation of multiple autonomous underwater vehicles based on improved ant colony algorithm

<b>[Objectives]</b> With the submarine topographic survey mission of the Multiple Autonomous Underwater Vehicles (MAUV) as the background,the optimal task allocation method of MAUV is proposed on the basis of an improved ant colony algorithm.<b>[Methods]</b> The task allocati...

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Bibliographic Details
Main Authors: LIU Ruixuan, ZHANG Yonglin
Format: Article
Language:English
Published: Editorial Office of Chinese Journal of Ship Research 2018-12-01
Series:Zhongguo Jianchuan Yanjiu
Subjects:
Online Access:http://www.ship-research.com/EN/Y2018/V13/I6/107
Description
Summary:<b>[Objectives]</b> With the submarine topographic survey mission of the Multiple Autonomous Underwater Vehicles (MAUV) as the background,the optimal task allocation method of MAUV is proposed on the basis of an improved ant colony algorithm.<b>[Methods]</b> The task allocation model is first established and the basic ant colony algorithm subsequently improved. The improved ant colony consists of multiple groups. In order to enhance the adaptive and global search ability of the algorithm,the ant selection method of the remaining task execution capability,new heuristic function and updated global pheromone method are improved. In local searches,the convergence rate of the optimal solution is further accelerated by the 2-opt algorithm.<b>[Results]</b> The Matlab simulation results show that the improved ant colony algorithm can effectively improve the task allocation efficiency of MAUV while also providing a good balance between the distance of the voyage and the cost of the consumption.<b>[Conclusions]</b> This article can provide references for submarine topographic survey mission assignment in real environments.
ISSN:1673-3185
1673-3185