摘要
针对水下航行器(AUV)因在水下的运动姿态调整能力有限,而导致路径规划与实际运行状况存在差距的问题,提出了一种自由运动方向的蚁群算法来进行路径规划,同时为提高算法收敛速度,提出基于信息素初始布置的改进蚁群算法。该算法设置了AUV在水下合理的转向角,并在此限制下自由选择运动方向;同时,采用有利前进方向判断和可视图法对人工势场法进行改进,规划出初始路径为改进蚁群算法进行信息素初始布置。仿真结果表明:改进的蚁群算法能有效缩短路径长度,并且能够适应复杂的动态环境。
Aiming at the problem that the path planning of underwater vehicle(AUV)has a gap with the actual running status due to its limited ability to adjust its motion posture under water,an ant colony optimization algorithm with free moving direction is proposed for path planning.At the same time,in order to improve the convergence speed of the algorithm,an improved ant colony optimization(IACO)based on pheromone initial arrangement is proposed.In this algorithm,a reasonable steering angle of AUV under water is set,and the moving direction is freely selected under this limit.At the same time,the artificial potential field method is improved by judging the favorable direction and visibility method,and the initial path is planned for the pheromone initial arrangement of the IACO.The simulation results show that the IACO can effectively shorten the path length and adapt to the complex dynamic environment.
作者
周鑫
徐荣武
程果
高端阳
ZHOU Xin;XU Rongwu;CHENG Guo;GAO Duanyang(Institute of Noise and Vibration,Naval University of Engineering,Wuhan 430033;National Key Laboratory on Ship Vibration and Noise,Wuhan 430033;Navigation System,Dalian Naval Academy,Dalian 116000)
出处
《舰船电子工程》
2023年第9期42-48,110,共8页
Ship Electronic Engineering
关键词
自由运动方向
人工势场法
蚁群算法
信息素初始布置
复杂动态环境
free direction of motion
artificial potential field(APF)
ant colony optimization(IACO)
pheromone initial arrangement
complex dynamic environment
