摘要
针对大规模无人机集群跟踪航线飞行时遇到障碍物的规避问题,提出了一种基于分布式模型预测控制结合视野和自适应避障半径的无人机集群避障算法。集群飞行过程中,无人机根据自身位置获取当前时刻的参考航线信息,通过局部信息交互获取周围邻居的预测轨迹,当遇到障碍物时,结合提出的自适应避障半径法以及视野拓扑,有效解决了集群避障时内部安全距离无法保持且部分无人机和障碍物发生碰撞的问题,实现了集群飞行的外部避障与内部防撞。
Aiming at the obstacle avoidance problem of large-scale UAV swarm tracking flight route,a swarm obstacle avoidance algorithm based on distributed model predictive control combined with visual field and adaptive obstacle avoidance radius is proposed.In the process of swarm flight,the UAV obtains the reference route information of the current moment according to its own position,and obtains the predicted trajectory of its neighbors through local information interaction.When encountering obstacles,the adaptive obstacle avoidance radius and field of view topology method are combined to effectively solve the problem that the internal safety distance cannot be maintained and some UAVs collide with obstacles during obstacle avoidance,the external obstacle avoidance and internal collision avoidance of swarm flight are realized.
作者
艾高航
李春涛
Ai Gaohang;Li Chuntao(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2024年第12期2945-2959,共15页
Journal of System Simulation
基金
国家自然科学基金(61903190)
中央高校基本科研业务费专项资金(NS2023016)
航空科学基金(2022Z023052003)。
关键词
无人机集群
避障
自适应避障半径
视野拓扑
分布式模型预测控制
UAV swarm
obstacle avoidance
adaptive obstacle avoidance radius
field of view topology
distributed model predictive control