改进微种群遗传算法在自主水下机器人路径规划中的应用

The application of Improved micro-Genetic Algorithm in Path Planning for AUV

研究了在静态环境条件下AUV(自主水下机器人)全局无碰撞的路径规划方法。提出运用顶点图像法建立环境模型,然后利用改进的微种群遗传算法得到一条从起点到终点的安全、无碰撞地绕过所有障碍物的最优路径,并且进行了AUV路径规划仿真实验和结果分析。仿真实验表明,本文采用的改进微种群遗传算法是正确和有效的,具有优化效果明显,运算速度快等优点。

This paper studies an approach to the global collision-free path planning for Autonomous Underwater Vehicle （AUV） in the static circumstance and proposes an environment model by vertex-image method, then uses the improved micro-Genetic Algo-rithm （μGA） 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 advance effect of optimization and can expedite operation by simulation.