改进A*算法在三维空间中无人机的航迹规划  

Improved Aalgorithm for UAV trajectory planning in 3D space

作　　者：姚千 杨洁[1] YAO Qian;YANG Jie(School of Mechanical and Transportation,Southwest Forestry University,Kunming 650224,China)

机构地区：[1]西南林业大学机械与交通学院,云南昆明650224

出　　处：《传感器与微系统》2025年第3期143-147,151,共6页Transducer and Microsystem Technologies

基　　金：云南省教育厅科学研究基金资助项目(111722038,111723084)。

摘　　要：为满足无人机在三维空间中的航迹规划,将原始A*算法的子节点搜索方式进行了改造处理,从原来的8个子节点变为26个子节点。试验发现,改造后的A*算法存在搜索时间长、子节点冗余等问题。为了提升算法的收敛速度,在此基础上,提出了方向索引的方法,通过优先收录目标点所在方向的区间节点,以达到压缩收录节点的数量,从而减少其计算量,并且引入贝塞尔曲线方法,对其输出的航迹进行了平滑处理,使其更符合实际的飞行要求。为验证方法的可行性,在MATLAB中,通过不同大小的栅格地图进行了多组对比试验。从试验的输出结果可以得出,优化后的A*算法速度提升了近55%,收录的节点数量减少近66%。In order to meet the UAV trajectory planning in 3D space,child-node search method of the original Aalgorithm is modified and processed,from the original 8 child-nodes to 26 child-nodes.Experiments reveal that the modified Aalgorithm has the problem of long search time and redundant child nodes.To improve the convergence speed of the algorithm,on this basis,a directional indexing method is proposed to compress the number of register nodes by prioritising the inclusion of interval nodes in the direction of the target point,in order to reduce its computation.And the Bessel curve method is introduced to smooth the output trajectory to make it meets the actual flight requirements better.In order to verify the feasibility of the method,several groups of comparison tests are conducted in MATLAB with different sizes of raster maps.It can be concluded from the output results of the tests that the speed of the optimized Aalgorithm is increased by nearly 55%,and the number of included nodes is reduced by nearly 66%.

关 键 词：航迹规划 三维A~*算法 方向索引 节点扩展 贝塞尔曲线 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] V279[自动化与计算机技术—计算机科学与技术]