摘要
为解决四旋翼无人机导航系统路径规划问题,提出了改进A^(*)搜索算法。该算法融合跳点搜索思想对地图进行剪枝操作,减少搜索空间;通过改变搜索方向判断机制、判别方向夹角与设定阈值的大小,限定搜索方向,减少搜索节点;引入碰撞检测机制,计算障碍物到无人机飞行路径的最小距离,提高其自主避障的可靠性。通过数据仿真对比改进A^(*)算法与传统A^(*)算法,验证改进A^(*)算法的可行性。搭建由T265双目相机和D435i深度相机作为视觉传感器的试验飞行平台,依据所构建出的障碍物地图进行实验验证,并对改进A^(*)算法与传统A^(*)算法路径规划结果进行对比分析。
In order to solve the path planning problem of quad-rotor UAV navigation system,an improved A^(*)search algorithm is proposed.The algorithm integrates the idea of skipping point search to prune the map to reduce the search space;changes the search direction judgment mechanism to determine the size of the direction angle and the set threshold,and limits the search direction to reduce search nodes;introduces a collision detection mechanism to calculate the minimum distance from obstacles to the drone's flight path to improve its autonomous obstacle avoidance reliability.The feasibility of the improved A^(*)algorithm is verified by comparing the improved A^(*)algorithm with the traditional A^(*)algorithm through data simulation.A test flight platform using a T265 binocular camera and a D435i depth camera as vision sensors was built.Experimental verification is carried out based on the constructed obstacle map,and the path planning results of the improved A^(*)algorithm and the traditional A^(*)algorithm are compared and analyzed.
作者
张永鑫
王磊
潘明然
郝勇汀
张茗宇
ZHANG Yong-xin;WANG Lei;PAN Ming-ran;HAO Yong-ting;ZHANG Ming-yu(School of Mechanical Engineering,Shenyang Ligong University,Shenyang 110159,China;R&D Center,Liaoshen Industries Group Co.,Ltd.,Shenyang 110045,China)
出处
《机械工程与自动化》
2024年第5期17-20,共4页
Mechanical Engineering & Automation
基金
辽宁省教育厅基本科研项目(LJKFZ20220186)
沈阳市中青年科技创新人才(RC200537)。
