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A Hierarchical Cooperative Mission Planning Mechanism for Multiple Unmanned Aerial Vehicles

机译:多种无人机的分层协同任务计划机制

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In this paper, the cooperative multi-task online mission planning for multiple Unmanned Aerial Vehicles (UAVs) is studied. Firstly, the dynamics of unmanned aerial vehicles and the mission planning problem are studied. Secondly, a hierarchical mechanism is proposed to deal with the complex multi-UAV multi-task mission planning problem. In the first stage, the flight paths of UAVs are generated by the Dubins curve and B-spline mixed method, which are defined as “CBC)” curves, where “C” stands for circular arc and “B” stands for B-spline segment. In the second stage, the task assignment problem is solved as multi-base multi-traveling salesman problem, in which the “CBC” flight paths are used to estimate the trajectory costs. In the third stage, the flight trajectories of UAVs are generated by using Gaussian pseudospectral method (GPM). Thirdly, to improve the computational efficiency, the continuous and differential initial trajectories are generated based on the “CBC” flight paths. Finally, numerical simulations are presented to demonstrate the proposed approach, the designed initial solution search algorithm is compared with existing methods. These results indicate that the proposed hierarchical mission planning method can produce satisfactory mission planning results efficiently.
机译:本文研究了多种无人机协同多任务在线任务计划。首先,研究了无人机的动力学特性和任务规划问题。其次,提出了一种层次化的机制来处理复杂的多无人机多任务任务计划问题。在第一阶段,无人机的飞行路径是通过杜宾斯曲线和B样条混合方法生成的,定义为“ CBC)”曲线,其中“ C”代表圆弧,“ B”代表B样条分割。在第二阶段,将任务分配问题解决为多基地多行销业务员问题,其中使用“ CBC”飞行路径来估算航迹成本。在第三阶段,通过使用高斯伪谱法(GPM)生成无人机的飞行轨迹。第三,为了提高计算效率,基于“ CBC”飞行路径生成了连续的和微分的初始轨迹。最后,通过数值仿真对所提方法进行了验证,并将设计的初始解搜索算法与现有方法进行了比较。这些结果表明,所提出的分级任务计划方法可以有效地产生令人满意的任务计划结果。

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