一种无人巡航船遍历多目标点的路径规划算法研究

A traversal multi-target path planning algorithm for unmanned cruise ship

针对无人巡航船遍历多目标点的路径规划问题,提出了一种混合的多目标点路径规划算法。首先,将多目标点路径规划问题转化为旅行商问题,并采用改进的灰狼优化算法规划出多目标点的最优巡航顺序。针对传统灰狼优化算法忽略环境因素的缺陷,通过在适应度函数中引入环境影响因子以反映障碍物和未知区域对路径规划的影响。然后,在上述规划好的多目标点巡航顺序的基础上,利用A*算法结合改进的人工势场法完成各个目标点之间的路径规划。针对传统人工势场法的目标不可达问题,通过优化斥力势场函数来解决。最后,分别在普通环境和复杂环境中与另外2种算法进行了仿真实验对比。实验结果分析表明,提出的算法是有效的,能够有效缩短路径规划时间,降低距离成本。

To solve the problem of traversal multi-goal path planning for unmanned cruise ships,a hybrid path planning method is proposed.This method is divided into two parts.Firstly,the multi-goal path planning problem is transformed into the travel salesman problem and an improved grey wolf optimizer(GWO)algorithm is used to calculate the multi-goal cruise sequence.In view of the unconsidered environmental factors in the traditional GWO algorithm,the environmental impact factors are introduced into the fitness function to reflect the impact of obstacles and unknown areas on multi-goal sequence planning.Secondly,based on the planned goal sequence,the A*algorithm is combined with the improved artificial potential field(APF)method to complete the single-goal path planning between each goal.The goal nonreachable problem of the traditional artificial potential field method is solved by the optimized repulsive potential function.Finally,the comparative simulation experiments with other two algorithms in ordinary and complex environment are carried out.The experimental results verifies the effectiveness of the proposed hybrid algorithm.Through the statistical analysis of experimental results,the proposed hybrid algorithm exhibits better performance than other two methods in terms of distance and time costs,and the effectiveness of the proposed hybrid algorithm is verified.