基于改进蚁群算法的受限水域无人船路径规划  

Path Planning of Unmanned Ships in Restricted Waterways Based on Improved Ant Colony Algorithm

作　　者：王桐[1] 马恺 WANG Tong;MA Kai(College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001)

机构地区：[1]哈尔滨工程大学信息与通信工程学院,哈尔滨150001

出　　处：《舰船电子工程》2023年第11期120-124,128,共6页Ship Electronic Engineering

基　　金：中央大学基础研究基金(编号:KY10800220073)资助。

摘　　要：为了解决智能船舶在内河水道、港口空间和海峡通道等受限水域规划路径时存在的转向角度过大,碰撞风险较高等问题,论文提出了一种基于改进蚁群算法的路径规划算法。该方法基于船舶转向角,碰撞危险度改进启发函数,综合计算路径转移概率;提出了一种基于距离因素的初始信息素浓度的分配策略以提高算法早期的搜索效率;同时提出自适应信息素挥发系数,进一步提升算法初期的收敛速度与全局搜索能力。在不同栅格环境下的仿真结果表明,改进的算法相较于传统蚁群算法在路径长度、转弯次数以及综合指标方面都有较明显的提升,同时算法的收敛性也得到了保障。在受限水域环境的仿真结果表明,论文提出的算法能有效避开碰撞风险较大的区域,提高了智能船舶路径规划的安全性。Aiming at solving the problems of excessive steering angle and high collision risk when intelligent ships plan their paths in restricted waterways,a path planning algorithm based on improved ant colony algorithm is proposed.The proposed algo⁃rithm improves the calculation of heuristic function and path transition probabilities by introducing ship steering angle and collision risk factors respectively.An allocation strategy of the initial pheromone concentration based on distance factor is proposed to im⁃prove the search efficiency of the algorithm.And then an adaptive pheromone volatilization coefficient is proposed to further improve the global search ability and the convergence speed in the early stage of the algorithm.The simulation results under different grid en⁃vironments show that compared with the traditional ACO,the proposed algorithm has obvious improvements in path length,steering times and comprehensive indicators,and the convergence of the algorithm is also guaranteed.The simulation results in the restricted waterways show that the proposed algorithm can effectively avoid the area with high collision risk and improve the safety of planned path.

关 键 词：受限水路 智能船舶 路径规划 蚁群算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]