摘要
针对传统A^(*)算法在无人机路径规划中存在的搜索效率低、贴近障碍物飞行和冗余节点和转折点较多的问题,提出一种改进的A^(*)算法。首先,引入地图尺寸与障碍物率两个参数的比值作为权重因子来改进启发式函数,提高搜索效率;其次,加入防碰撞策略,使无人机与障碍物始终保持一定的安全距离,提高路径的安全性;最后,采用冗余节点优化策略优化路径,减少转折点,使规划的路径更平滑。仿真结果表明,在相同尺寸栅格地图中,与传统A^(*)算法相比,改进后的A^(*)算法搜索效率、安全性均有提高,冗余节点数下降,路径更优。
Aiming at the problems of traditional A^(*)algorithm in unmanned aerial vehicle path planning,such as low search efficiency,flying close to obstacles and many redundant nodes and turning points,an improved A^(*)algorithm is proposed.Firstly,the heuristic function is improved by introducing the ratio of map size and obstacle rate as the weight factor to improve the search efficiency;Secondly,the anti-collision strategy is added to keep a certain safe distance between the unmanned aerial vehicle and obstacles and improve the safety of the path;Finally,the redundant node optimization strategy is used to optimize the path,which reduces the turning point and makes the planned path smoother.Simulation results show that in the same size grid map,compared with the traditional A^(*)algorithm,the improved A^(*)algorithm has improved search efficiency and security,reduced the number of redundant nodes,and better path.
作者
贾彬
包长春
蒋金成
JIA Bin;BAO Changchun;JIANG Jincheng(Inner Mongolia University of Technology,Institute of Aeronautics and Astronautics,Hohhot Inner Mongolia 010010,China)
出处
《信息与电脑》
2023年第19期71-75,共5页
Information & Computer
基金
内蒙古自治区科技计划项目“5G智慧高速公路运营大数据智能分析及决策关键技术研究”(项目编号:2022YFSJ0040)。
关键词
无人机
路径规划
A^(*)算法
启发式函数
unmanned aerial vehicle
path planning
A^(*)algorithm
heuristic function