Multi-Underwater Gliders Coverage Path Planning Based on Ant Colony Optimization

被引:13
作者
Ji, Haijun [1 ]
Hu, Hao [1 ]
Peng, Xingguang [1 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Peoples R China
基金
中国国家自然科学基金;
关键词
ant colony optimization; underwater glider; coverage path planning; ALGORITHM; AREAS;
D O I
10.3390/electronics11193021
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Underwater gliders (UGs) are widely applied to regional exploration to find potential targets. However, the complex marine environment and special movement patterns make it difficult to plan their coverage path. In this paper, a novel multi-underwater gliders coverage path planning algorithm based on ant colony optimization (MGCPP-ACO) is proposed. First, according to the detection radius of the sonar and the motion process of the UGs, we establish a detection coverage model. Then, considering the motion constraints of the UGs and optimization objectives, we redesign the feasible region, transition probability, pheromone update rule and heuristic function of the ACO algorithm. Finally, we carry out three groups of experiments. The simulation results show that the MGCPP-ACO can cover almost the entire sea area and adapt to different initial positions and heading angles. In addition, compared with the traditional scan-line (SCAN) algorithm, the MGCPP-ACO has a higher coverage efficiency and lower coverage cost.
引用
收藏
页数:14
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