基于改进双种群遗传算法的AUV路径规划方法研究

研究了在静态环境条件下AUV全局无碰撞的路径规划方法,提出了一种将顶点图像法与双种群遗传算法相结合的路径规划方法。利用顶点图像法建立环境模型,对候选路径进行二进制编码,然后利用改进的双种群遗传算法进行路径寻优。仿真实验表明,本文采用的改进双种群遗传算法是正确和有效的,具有运算速度快、全局优化能力强等优点。

Improved Double Populations Genetic Algorithm Based on Path Planning for AUV

This paper studies an approach to the global collision-free path planning for Autonomous Underwater Vehicle（AUV） in the static circumstance with the vertex-image method and the double populations genetic algorithm,and proposes an environment model by vertex-image method,then uses the improved Double Populations Genetic Algorithm（DPGA） to find a shortest path from the source position to the destination position for AUV.Simulation experiments and results are given in this paper.The approach is proved to be valid and feasible,and can obviously expedite operation and advance effect of global optimization by simulation.