复杂地形含禁区时，无人机可自动规划全覆盖安全路径。
UAV survey coverage path planning of complex regions containing exclusion zones
- 用多边形分解与深度优先搜索合并子区域
- 生成连续栅栏式覆盖路径，避让障碍物
- 适合有复杂边界和禁区的航测任务
本文针对包含禁区或障碍物的复杂凹多边形区域，解决无人机航拍覆盖路径规划问题。现有规划器多仅适用于简单凸多边形，而本研究提出新方法处理边界分裂、合并及内部孔洞等复杂情况。首先采用多边形分解技术将目标区域划分为凸子区域，再通过深度优先搜索算法合并为连通分量，并基于连通组件生成连续的Boustrophedon覆盖路径。利用直线骨架法对多边形进行偏移，确保无人机与禁区保持恒定安全距离。该方法可实现复杂几何约束环境下无人机的有效路径规划。
原文摘要 · Abstract (English)
This article addresses the challenge of UAV survey coverage path planning for areas that are complex concave polygons, containing exclusion zones or obstacles. While standard drone path planners typically generate coverage paths for simple convex polygons, this study proposes a method to manage more intricate regions, including boundary splits, merges, and interior holes. To achieve this, polygonal decomposition techniques are used to partition the target area into convex sub-regions. The sub-polygons are then merged using a depth-first search algorithm, followed by the generation of continuous Boustrophedon paths based on connected components. Polygonal offset by the straight skeleton method was used to ensure a constant safe distance from the exclusion zones. This approach allows UAV path planning in environments with complex geometric constraints.
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