Ship Motion Planning for MASS Based on a Multi-Objective Optimization HA* Algorithm in Complex Navigation Conditions

被引:6
|
作者
Wu, Meiyi [1 ]
Zhang, Anmin [1 ,2 ]
Gao, Miao [1 ]
Zhang, Jiali [1 ]
机构
[1] Tianjin Univ, Sch Marine Sci & Technol, Tianjin 300072, Peoples R China
[2] Tianjin Port Environm Monitoring Engn Ctr, Tianjin 300072, Peoples R China
基金
中国国家自然科学基金;
关键词
motion planning; MASS; multi-objective optimization; complex navigation conditions; UNMANNED SURFACE VEHICLE; A-ASTERISK; SIMULATION;
D O I
10.3390/jmse9101126
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Ship motion planning constitutes the most critical part in the autonomous navigation systems of marine autonomous surface ships (MASS). Weather and ocean conditions can significantly affect their navigation, but there are relatively few studies on the influence of wind and current on motion planning. This study investigates the motion planning problem for USV, wherein the goal is to obtain an optimal path under the interference of the navigation environment (wind and current), and control the USV in order to avoid obstacles and arrive at its destination without collision. In this process, the influences of search efficiency, navigation safety and energy consumption on motion planning are taken into consideration. Firstly, the navigation environment is constructed by integrating information, including the electronic navigational chart, wind and current field. Based on the environmental interference factors, the three-degree-of-freedom kinematic model of USVs is created, and the multi-objective optimization and complex constraints are reasonably expressed to establish the corresponding optimization model. A multi-objective optimization algorithm based on HA* is proposed after considering the constraints of motion and dynamic and optimization objectives. Simulation verifies the effectiveness of the algorithm, where an efficient, safe and economical path is obtained and is more in line with the needs of practical application.</p>
引用
收藏
页数:20
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