HU Chunlei, ZHANG Fei, ZENG Qingjun. Global path planning algorithm for AUV based on multi-objective ant colony strategy[J]. 2020, (11): 107-109+113. DOI: 10.13873/J.1000-9787(2020)11-0107-03.
基于多目标蚁群策略的AUV全局路径规划算法
摘要
为克服传统路径规划以路程长度为单一目标的局限性
提出一种海洋环境下水下机器人(AUV)路径规划的多目标蚁群算法
以航线距离、能量消耗、安全航行为综合规划目标。对传统航行距离因子启发函数进行改进
加快算法收敛速度
同时增加能耗因子、航道安全性因子构建综合启发函数
以满足多目标航行的需求;将信息素进行分类
基于不同目标性能排序改进信息素更新机制
并引入Pareto解集思想
寻得不同航行目标下的最优路径
提升解的全面性。仿真结果验证了改进算法的可行性和有效性。
Abstract
In order to overcome the limitation of the traditional path planning with the single goal of distance length
a multi-objective ant colony algorithm for autonomous underwater vehicle( AUV) path planning in ocean environment is proposed
which integrates route distance
energy consumption and safe navigation behavior. The traditional ant colony algorithm with distance factor as heuristic function is improved to accelerate the convergence speed of the algorithm
at the same time
energy consumption factor and channel safety factor are added to construct a comprehensive heuristic function to meet the needs of multi-objective navigation; classifying pheromones and improving pheromone updating mechanism based on performance ranking of different targets
and introduce the Pareto disassembly
finding the optimal path under different navigation objectives. The simulation results verify the feasibility and effectiveness of the improved algorithm.