摘要
在现代战争中,由于单架无人机完成任务有限,无人机集群系统应运而生。如何在拥挤的低空领域中实现无人机集群协同飞行且避障是无人机集群系统需要解决的重要问题之一。针对这一问题,设计了可实现无人机集群协同飞行且在飞行中实现障碍物避障的算法,该算法基于无人机编队中的长机-僚机法及集群智能的粒子群算法,实现了无人机集群协同飞行,同时采用人工势场法实现障碍物避障。将1架长机与4架僚机协同飞行进行仿真测试,通过飞行运动轨迹图和无人机分布测试结果观测出,算法满足在静态环境条件下,无人机集群在长机带领下实现集群协同飞行,并自主规避障碍物,且所有无人机均可到达飞行终点,验证了算法具有正确性和鲁棒性。
In the modern war,due to the limited task of a single UAV,the UAV swam system emerges as the times require.In low altitude area,how to achieve cooperative flight and obstacle avoidance is one of the most important problems in UAV swarm system.To solve this problem,this paper design an algorithm which can realize cooperative flight and obstacle avoidance of multiUAVs flight.In this paper,the particle swarm optimization(PSO)and the Leader-Follower method is used to realize the cooperative flight,and the artificial potential field method is used to avoid obstacles.One leader and four followers cooperative flight are simulated and tested,through the cooperative flight trajectory diagram and the UAV location distribution diagram,the algorithm designed in this paper satisfies that under static conditions,the UAV swarm can autonomously complete complex task,under the leadership of the leader,UAV swarm can achieve cooperative flight,autonomously avoid obstacles,and all UAV can reach the flight destination,the correctness and robustness of the algorithm is verified.
作者
申海
于长敏
林雨奇
SHEN Hai;YU Changmin;LIN Yuqi(College of Physical Science and Technology,Shenyang Normal University,Shenyang 110034,China)
出处
《沈阳师范大学学报（自然科学版）》
CAS
2022年第2期133-140,共8页
Journal of Shenyang Normal University:Natural Science Edition
基金
国家自然科学基金资助项目(12075158)
辽宁省科技厅自然科学基金指导计划项目(2019-ZD-0480)
沈阳市中青年科技创新人才支持计划项目(RC200334)
关键词
无人机集群
粒子群算法
长机-僚机法
人工势场法
协同飞行
UAV swarm
particle swarm optimization
leader-follower
artificial potential field
cooperative flight
