基于EMSDBO算法的无人机三维航迹规划  

Three-dimensional path planning of UAV based on EMSDBO algorithm

作　　者：隋东[1] 杨振宇 丁松滨[1] 周婷婷 SUI Dong;YANG Zhenyu;DING Songbin;ZHOU Tingting(College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学民航学院,江苏南京211106

出　　处：《系统工程与电子技术》2024年第5期1756-1766,共11页Systems Engineering and Electronics

基　　金：中国民用航空局资助项目([2022]125号);南京航空航天大学科研与实践创新计划(xcxjh20220730)资助课题。

摘　　要：针对无人机(unmanned aerial vehicle,UAV)三维航迹规划问题,提出一种增强型多策略蜣螂算法的UAV航迹规划方法。首先,将飞行接近率和响应时间的动态约束添加到威胁成本代价中,并考虑UAV转弯性能的影响,建立三维任务空间模型与航迹代价函数。其次,在蜣螂算法中引入偏移估计策略、变螺旋搜索策略、准反向学习策略和逐维变异策略,提高算法的全局寻优能力和收敛速度。最后,给出了改进算法在三维环境下航迹规划的仿真结果。结果表明:综合考虑UAV机动性能和转弯性能,规划出的路径可以更加安全有效地避开危险源。相比其他算法,改进算法的寻优能力更好,规划的航迹质量更优。In view of the unmanned aerial vehicle(UAV)three-dimensional path planning problem,an enhanced multi-strategy dung beetle algorithm of UAV path planning is proposed.Firstly,constraints on the flight proximity rate and response time are introduced and added to the threat cost,considering the influence of UAV turning performance,a three-dimensional task space model and trajectory cost function are established.Secondly,the dung beetle algorithm is enhanced by introducing offset estimation strategy,variable spiral search strategy,quasi-inverse learning strategy,and dimensional mutation strategy to improve the algorithm’s global optimization capability and convergence speed.Finally,simulation results of the improved algorithm for three-dimensional trajectory planning in an environment are presented.Results demonstrate that by considering both the maneuverability and turning performance of the UAV,the planned path can safely and efficiently avoid hazards.Compared to other algorithms,the enhanced multi-strategy dung beetle algorithm shows better optimization capability and generates higher-quality trajectories.

关 键 词：无人机 路径规划 飞行接近率 蜣螂优化算法 

分 类 号：V249[航空宇航科学与技术—飞行器设计]