基于蚁群算法的多AUV路径规划仿真研究

Simulation of Path Planning of Multiple Autonomous Underwater Vehicles(AUVs) Based on Ant Colony Algorithm

多AUV路径规划是一种典型的带约束组合优化问题,如果采用传统的方法求解效果并不理想。蚁群算法是对自然界中蚂蚁在寻找食物过程中所表现出来的智能行为的一种模拟,它非常善于处理带约束的大规模复杂组合优化问题。应用蚁群算法结合TSP问题来为一群AUV进行路径规划,寻找最短且安全的路径。算法分为两部分:1)路径优化:使所有AUV的总路程最小化;2)路径校核:检查是否存在潜在的静态或动态碰撞。最后以三个AUV的情形为例对算法加以了验证,仿真结果表明该方法耗时短、效率高,为求解多AUV路径规划问题提供了一个高效解决方案。

Path planning of multiple AUVs is a typical constrained combinational optimization problem which is difficult to tackle with conventional methods. Ant colony algorithm, which is simulation of intelligent behavior exhibited by real ant colonies during their food hunting, provides an efficient way for large - scale complicated combinational optimization subject to nonlinear constraints. In this paper, ant colony algorithm is combined with TSP to find economical and safe routes for a swarm of AUVs. The algorithm can be divided into two phases ： 1 ） route optimization ： minimizing the total journey of the vehicles and 2 ） route validation： checking whether there exist stationary and/or moving collisions. A case study for three AUVs to survey a given area is also presented and the simulation results show that the proposed algorithm provides an efficient and timesaving way for path planning of multiple AUVs.