多UAV协同区域覆盖搜索研究

Research on Multiple UAV Cooperative Area Coverage Searching

针对多无人机协同区域覆盖搜索问题,为降低问题求解的复杂度,将其分解为多UAV任务区域分配和完全覆盖路径规划两个子问题,对子问题分别优化求解。建立了无人机任务执行代价模型,采用分层模糊推理求解无人机的性能评估指数,根据性能评估指数采用基于面积的区域分割方法实现多无人机搜索任务区域的分配。分析了无人机实现区域内覆盖搜索的最优路径问题,给出了在特定多边形区域下最小代价的搜索模式和搜索路径。仿真实验结果验证了所给方法的有效性。

Focusing on the problem of cooperatively searching a given area to detect objects of interest, using multiple heterogenous unmanned aerial vehicles （UAVs）. the whole problem was divided into two sub-problems, which are cooperative mission area assignment and coverage route planning, to find optimal solution to the sub-problems respectively, The cost model of UAV＇s mission execution was established and a new approach to UAV＇s relative capabilities assessment was proposed using hierarchical fuzzy inference. The whole mission area was divided based on the results of UAV capabilities assessment and initial locations using polygon area decomposition, and the resulting areas were assigned among the UAVs. The optimal searching pattern was analyzed and a best searehing route-was given to cover the UAV mission area, Simulation results demonstrate the validity of the approach,