基于改进遗传算法的无人艇集群多任务分配路径规划
Global Path Planning for Multi-Task Assignment Based on Improved Genetic Algorithm for Multi-USV
王志洋 1王龙金1
作者信息
- 1. 青岛科技大学机电工程学院,山东青岛 266000
- 折叠
摘要
为完成多任务的分配并确保USV集群航行的总路径最短,同时确保各USV的路径长度差距最小,针对USV集群全局路径规划问题从初始种群生成方法、选择算子和变异算子等3方面对遗传算法进行改进.针对航行区域障碍物特点,采用切线法对改进遗传算法生成的路径进行优化.为验证算法的有效性,基于MATLAB/Simulink仿真平台构建仿真模型,并针对具体航行环境进行多任务全局路径规划测试.仿真结果显示,所提出的算法可实现USV集群多任务分配的全局路径规划.
Abstract
In order to complete the assignment of multiple tasks,the shortest total path of unmanned surface vehicle(USV)cluster navigation and the shortest path length gap of each USV are ensured,the genetic algorithm is improved from three aspects of initial population generation,selection and mutation operator.According to the characteristics of obstacles in navigation area,the tangent method is used to optimize the path generated by improved genetic algorithm.In order to verify the effectiveness of the algorithm,a simulation model is built based on MATLAB/Simulink simulation platform,and the multi-task global path planning test is carried out according to the specific navigation environment.The proposed algorithm can realize the global path planning of USV cluster multi-task assignment as the simulation results showed.
关键词
无人艇集群/改进遗传算法/多任务分配/路径规划Key words
multi-unmanned surface vehicle(USV)/improved genetic algorithm/multitasking/path planning引用本文复制引用
出版年
2024
NETL
NSTL
万方数据