摘要
由于路径规划问题,无人机起始点与目标点的距离在5 000-5 500 m内,导致飞行耗时较长。因此,本文提出一种基于多目标搜索的无人机协同轨迹智能规划方法。该方法将双坐标系做为量化基准,构造无人机动力学模型;通过蚁群算法,规划无人机运行的初始路径;进行多目标搜索,实现无人机协同轨迹智能规划。经对比实验,设置威胁源,获取相应的飞行耗时数据。对比数据可知,该方法的飞行耗时低于原有方法,实现了性能上的突破。
Since the distance between the starting point and the target point is within the range of 5000 meters to 5500 meters,there is a problem of long flight time.Therefore,an intelligent planning method for UAV collaborative trajectory based on multitarget search is proposed.The dual coordinate system is used as a quantitative benchmark to construct the UAV dynamic model;the initial path of the UAV is planned through the ant colony algorithm;the multi-target search is performed to realize the intelligent planning of the UAV coordinated trajectory.Design comparative experiments,set threat sources,and obtain corresponding flight time-consuming data.The comparison data shows that the flight time of this method is lower than that of the original method,achieving a breakthrough in performance.
作者
寇丽君
KOU Lijun(Dalian Neusoft University of Information,Dalian Liaoning 116000,China)
出处
《智能计算机与应用》
2020年第11期180-181,186,共3页
Intelligent Computer and Applications
关键词
多目标搜索
无人机
协同轨迹智能规划
动力学模型
multi objective search
UAV
cooperative trajectory intelligent planning
dynamic model
