基于蚁群算法的AUV全局路径规划方法

Global Planning Path Method of AUV Based on Ant Colony Optimization Algorithm

在大范围海洋环境中,应用蚁群算法对自主式水下潜器(AUV)的全局路径规划问题进行了研究。基于栅格环境模型建立了蚁群可视图模型,设计了蚁群信息素更新规则;给出了蚁群全局路径规划的操作步骤;针对蚁群规划路径不平滑问题,设计了切割算子和插点算子。仿真实验结果表明,蚁群全局规划算法非常适合于求解复杂环境中的规划问题,规划时间短、路径平滑。

Global path planning chart data is investigated b problem for autonomous unde y using ant colony optimization troduces intervisibility graph based on grid environment rwater vehicle （AUV） based on large-scale （in shorts, ACO） algorithm. This paper inmodel and designs an ectohormone updating rule for ACO algorithm. The operating steps of ACO are proposed for global planning path of AUV. In allusion to solve the problem that the planned path is not smooth, a cutting operator and an inserting-point operator are designed in the paper. The simulating results demonstrate that the ACO algorithm is very suitable for solving the question of global path planning for AUV in complex oceanic environment which has a lot of obstacles in the grid model. And the optimizing time of ACO path planning algorithm is very short and the path is very smooth.