多固定翼无人机的任务分配和路径规划算法  

Task Allocation and Path Planning Algorithms for Multi-Fixed-Wing UAV

作　　者：郭家赫 高岳林 柳迎春 GUO Jiahe;GAO Yuelin;LIU Yingchun(College of Computer Science and Engineering,North Minzu University,Yinchuan,Ningxia,China;College of Mathematics and Information Science,North Minzu University,Yinchuan,Ningxia,China;Ningxia Key Laboratory of Intelligence Information and Big Data Processing,Yinchuan,Ningxia,China)

机构地区：[1]北方民族大学计算机科学与工程学院,宁夏银川 [2]北方民族大学数学与信息科学学院,宁夏银川 [3]宁夏智能信息与大数据处理重点实验室,宁夏银川

出　　处：《太原理工大学学报》2025年第2期348-355,共8页Journal of Taiyuan University of Technology

基　　金：宁夏自然科学基金重点项目(2022AAC02043);宁夏高等教育一流学科建设基金项目(NXYLXK2017B09);北方民族大学重大科研专项项目(ZDZX201901);南京证券支持基础学科研究项目(NJZQJCXK202201)。

摘　　要：【目的】多固定翼无人机(Unmanned Aerial Vehicle,UAV)的任务分配和路径规划问题中,将固定翼UAV简单地视为质点,未考虑自身航向角、初始和终止速度向量等问题。针对多固定翼UAV任务规划问题,将改进的蚁群算法(Ant Colony Optimization,ACO)和自组织映射(Self-Organizing Map,SOM)算法相结合,提出ACO-SOM算法应用于多无人机系统。【方法】通过SOM进行任务分配,引入蚁群状态转移概率方法,调整SOM获胜神经元的权值,使得固定翼UAV按照最优Dubins路线依次到达各个目标点。根据巡航能力和运动学约束合理分配任务,构造多目标优化函数,实现多固定翼UAV的协同执行任务能力。【结果】分别在障碍物、不同起落点场景下对ACO-SOM算法进行仿真验证,实验结果表明,该方法能使多固定翼UAV合理任务分配并规划出最优路径,具有较高的避障和规划能力。【Purposes】The task allocation and path planning of multi-fixed-wing Unmanned Aerial Vehicle(UAV)simply regard it as a particle,thus the problems of ignoring its own heading angle,initial and terminal velocity vectors exist.Aiming at the problem of multi-fixed-wing UAV mission planning,improved Ant Colony Optimization(ACO)algorithm and Self-Organizing Map(SOM)algorithm are combined to propose ACO-SOM algorithm for multi-UAV system.【Methods】The SOM was used for task allocation,and the ant colony state transition probability method was introduced to adjust the weights of SOM winning neurons,so that the fixed-wing UAV reached each task point in turn according to the optimal dubins route.According to the cruise ability and kinematic constraints,the tasks were reasonably allocated,and the multi-objective optimization function was constructed to realize the cooperative task execution ability of multiple fixed-wing UAVs.The ACO-SOM algorithm was simulated and verified in the scenarios of obstacles and different landing points.【Findings】Experimental results show that,compared with SOM,the proposed method can make the multi-fixed-wing UAV reasonably assign tasks and plan the optimal path,and has higher obstacle avoidance and planning abilities.

关 键 词：任务分配 路径规划 固定翼无人机 自组织映射 蚁群算法 Dubins曲线 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]