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Assigning Micro UAVs to Task Tours in an Urban Terrain

机译:将微型无人机分配给城市地形中的任务巡视

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摘要

An optimization algorithm for assigning in realtime multiple unmanned aerial vehicles (UAVs) to task tours is presented and tested as part of a flight demonstration program. The scenario of interest is one where multiple microaerial vehicles are launched from a small UAV in order to investigate selected targets in an urban terrain. For path planning, we use the Dubin''s car model so that the vehicles'' dynamic constraint of minimum turning radius is taken into account. Due to the prohibitive computational complexity of the coupled path optimization and assignment problem, we solve the problem by ordering a set of tasks based on the Euclidean distance, utilizing a traveling salesman problem solver. We apply upper and lower bounding procedures iteratively on active subsets within the set of feasible group assignments, enabling efficient search of the solution space. The online implementation of the algorithm is discussed and simulation results confirm the efficiency of the proposed algorithm. Results from recent flight tests are also provided.
机译:作为飞行演示程序的一部分,提出并测试了一种用于实时分配多架无人机(UAV)到任务巡逻的优化算法。感兴趣的场景是从小型无人机发射多架微型飞机以调查城市地形中选定的目标的场景。对于路径规划,我们使用Dubin的汽车模型,以便考虑车辆的最小转弯半径的动态约束。由于耦合路径优化和分配问题的计算复杂性过高,我们使用旅行商问题求解器通过基于欧几里得距离排序一组任务来解决该问题。我们对可行组分配内的活动子集反复应用上限和下限过程,从而可以高效地搜索解决方案空间。讨论了该算法的在线实现,仿真结果证实了该算法的有效性。还提供了最近飞行测试的结果。

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