基于蚁群算法的水下潜器全局路径规划技术研究

Research on Global Path Planning of Underwater Vehicle Based on Ant Colony Algorithm

全局路径规划是水下潜器智能控制的关键技术之一,其任务是在已知障碍物的环境中按照某一最优指标寻找一条从起始点到目标点的无碰路径。文章使用蚁群算法对水下潜器三维空间全局路径规划问题进行了研究,讨论了三维空间的抽象环境建模方法,依据安全性、经济性和路径最短原则设计了算法适应值评价函数,综合利用迭代最优和全局最优信息设计了信息素更新规则,仿真结果验证了算法的正确性和有效性。

Global path planning is one of the key techniques of underwater vehicle＇s intelligent control system, whose purpose is to find a collision-free path from the source position to the destination position according to some optimization criteria. The ant colony algorithm is used when studying the global path planning for underwater vehicle in three-dimensional space. The methods for abstract modeling in three-dimensional space were described. In light of the rule of security, economy and the shortest path, the fitness evaluation function was designed while pheromone updating rules, which synthesized iteration-best information and global-best information, were given as well The simulation result proves the correctness and effectiveness of the algorithm designed.