基于优化A*和MPC融合算法的三维无人机航迹规划  

3D UAV trajectory planning based on optimized A*and MPC fusion algorithm

作　　者：宋超 李波[1] 马云红[1] 黄晶益 SONG Chao;LI Bo;MA Yunhong;HUANG Jingyi(School of Electronics and Information,Northwestern Polytechnical University,Xi’an 710072,China)

机构地区：[1]西北工业大学电子信息学院,陕西西安710072

出　　处：《系统工程与电子技术》2023年第12期3995-4004,共10页Systems Engineering and Electronics

基　　金：国家自然科学基金(62003267);航空科学基金(20200020053002);陕西省重点研发计划项目(2023-GHZD-33);电磁空间作战与应用重点实验室(2022ZX0090)资助课题。

摘　　要：针对传统A*算法在二维无人机(unmanned aerial vehicle,UAV)航迹规划中存在的不足,提出了一种优化A*算法与模型预测控制融合的三维UAV航迹规划方法。通过压缩搜索空间和平滑处理,提出了一种基于三维空间的优化A*算法,综合考虑全局规划与实时避障需求,构建了优化A*算法与模型预测控制的融合算法。仿真验证表明,融合算法能够实现三维复杂环境下UAV实时避障航迹规划,搜索节点少,路径长度短且更加平滑,具有很好的环境适应性。In view of the shortcomings of the traditional A*algorithm in 2D unmanned aerial vehicle(UAV)trajectory planning,a 3D UAV trajectory planning method that fuses the optimized A*algorithm with model predictive control is proposed.An optimized A*algorithm based on 3D space is proposed by compressing the search space and smoothing operation,and a fusion algorithm of optimised A*algorithm and model predictive control is constructed by considering the global planning and real-time obstacle avoidance requirements.Simulation verification shows that the proposed fusion algorithm can achieve real-time UAV obstacle avoidance trajectory planning in 3D complex environment,with fewer search nodes,shorter and smoother path lengths,and has good environmental adaptability.

关 键 词：无人机航迹规划 优化A*算法 模型预测控制 三维空间模型 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]