摘要
在进行无人机低空飞行的路径规划时,障碍物已不能简单的简化为点状;针对该问题,首先将带有面状障碍物的图片格式地图以像素为单位进行栅格划分,在定义了栅格距离后,进行距离变换,并运用边界跟踪方法生成栅格空间V图;其次,将A-Star算法的启发思想引入到蚁群算法中,并修改了启发信息计算公式以使蚁群算法更适合于栅格空间优化;最后,以栅格空间V图为初始路径,运用改进的蚁群算法进行优化选择,得到了满意的路径规划结果。
When the UAVs fly at a low altitude, the obstacles should not be simplified as points. To solve this problem, firstly the map picture is split into grids in the level of pixels, after defining the distance between the grids, the map picture is mapped into the grid space and the V-diagram is constructed using the edge tracking method. Secondly, we introduce the heuristic information used in the A-Star algorithm into the Ant Colony System, and modified the formula for the calculation of the amount of the heuristic information. Finally, using this modified Ant Colony System, a satisfying route planning result is achieved.
出处
《计算机测量与控制》
CSCD
北大核心
2009年第6期1212-1214,共3页
Computer Measurement &Control
关键词
栅格
V图
蚁群算法
无人机
路径规划
grid
V-diagram
Ant colony system
UAV
route planning
