小型无人机协同覆盖侦察路径规划

Cooperative coverage path planning for small UAVs

针对多架小型无人机对含有障碍的区域覆盖侦察最佳路径规划问题,首先用方形单元格将待侦察区域离散化,利用基于初始位置的划分方法划分出与无人机对应的子区域,把问题转化为单无人机优化问题以降低计算复杂度;然后在最小生成树的基础上提出节点交换法,对各子区域的形状和最小生成树进行调整优化;最后依据优化后的最小生成树为每个子区域构建侦察路径。仿真验证了该方法产生的规划路径能够完全覆盖指定区域且无重叠,路径长度和转弯数最小。

Our target is finding the optimal coverage path planning (CPP) in given area including obstacles for multi small unmanned air vehicles (UAV). First, the given area is discretized into cells. And to degrade the computation complexity, the divide areas based on robots initial positions (DARP) algorithm is utilized to divide the area into separated equal subareas, transforming the multi-CPP problem into several CPP problems. Then, an end nodes exchanged method based on minimum spanning trees is proposed to adjust the shape of subareas and minimum spanning trees. Finally, the coverage paths of each subareas are constructed based on the optimized minimum spanning trees. And the simulation confirms that the proposed method can guarantee the completeness , non-overlaps, minimum lengths and the least number of turns.