摘要
针对A^(*)算法在复杂环境下规划时间长、路径转折点多及生成路径不平滑的问题,提出一种基于自适应权重的三维A^(*)路径规划(3D A^(*)path planning based on Adaptive Weights,3D A^(*)-AW)改进算法。首先,在曼哈顿距离作为启发函数的基础上引入无人机位置信息,设计自适应权重评价函数提高算法收敛速度。其次,根据拐点信息二次优化路径长度,删除不必要的拐点,生成最优路径。最后,搭建三维模拟环境进行仿真验证。实验结果表明,相比A^(*)算法,改进算法在规划时间、搜索范围、路径长度以及平滑度方面均有所改善。
For the problems of long planning time,many turning points in the path,and the generated paths are not smooth under complex environments,a 3D A^(*)path planning algorithm based on adaptive weights(3D A^(*)-AW)is proposed.Firstly,the umanned aerial rehicle(UAV)position information is introduced on the basis of Manhattan distance as the heuristic function,and the adaptive weighting evaluation function is designed to improve the convergence speed of the algorithm;secondly,the path length is optimized for a second time based on the inflection point information,unnecessary inflection points are deleted,and the optimal path is generated;finally,a 3D simulation environment is built to verify the algorithm.Experiment results show that the improved algorithm is more efficient and applicable in terms of planning time,search range,path length,and smoothness than the traditional A^(*)algorithm.
作者
梁青
周璐
吕文凯
周惠珂
LIANG Qing;ZHOU Lu;LYU Wenkai;ZHOU Huike(School of Electronic Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710121,China)
出处
《西安邮电大学学报》
2022年第3期84-89,共6页
Journal of Xi’an University of Posts and Telecommunications
基金
陕西省自然科学基金项目(2018GY-150)。
